We are thrilled to announce that TrueFoundry has raised $19M in Series A funding, led by Intel Capital, with participation from Spark Capital, Pi Ventures, and others.
What We Do
AI deployment today is painfully slow, expensive, and requires large engineering teams. At TrueFoundry, we\u2019re fixing this by building an autonomous AI deployment layer that lets ML teams ship models 10x faster with minimal infra effort. Our "Agent on Autopilot" dynamically optimizes AI workloads\u2014handling infra scaling, cost management, and performance tuning automatically.
Why This Matters
1. DevOps-free AI Deployment \u2013 No need to manually tweak infra.\n 2. Automated Scaling & Cost Optimization \u2013 Get the best performance at the lowest cost.\n 3. Works with Existing Stacks \u2013 Supports Kubernetes, AWS, GCP, and on-prem.\nThis funding will help us:
1. Expand our AI agent capabilities for self-optimizing ML workflows.\n 2. Integrate with more platforms & LLM frameworks.\n 3. Scale our engineering team\u2014we're hiring! (If you love ML infra, let\u2019s talk!??? )\nWould be great to hear from the HN community! What are your biggest AI infra pain points? Let\u2019s discuss!"},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Show HN: TrueFoundry raises $19M Series A to scale AI deployment with agents"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://www.truefoundry.com/blog/announcing-our-19m-series-a-scaling-ai-deployment-with-autonomous-agents-on-autopilot"}},"_tags":["story","author_supreetgupta","story_42967374","show_hn"],"author":"supreetgupta","children":[42967397],"created_at":"2025-02-06T23:03:17Z","created_at_i":1738882997,"num_comments":0,"objectID":"42967374","points":3,"story_id":42967374,"story_text":"Hey HN,
We are thrilled to announce that TrueFoundry has raised $19M in Series A funding, led by Intel Capital, with participation from Spark Capital, Pi Ventures, and others.
What We Do
AI deployment today is painfully slow, expensive, and requires large engineering teams. At TrueFoundry, we\u2019re fixing this by building an autonomous AI deployment layer that lets ML teams ship models 10x faster with minimal infra effort. Our "Agent on Autopilot" dynamically optimizes AI workloads\u2014handling infra scaling, cost management, and performance tuning automatically.
Why This Matters
1. DevOps-free AI Deployment \u2013 No need to manually tweak infra.\n 2. Automated Scaling & Cost Optimization \u2013 Get the best performance at the lowest cost.\n 3. Works with Existing Stacks \u2013 Supports Kubernetes, AWS, GCP, and on-prem.\nThis funding will help us:
1. Expand our AI agent capabilities for self-optimizing ML workflows.\n 2. Integrate with more platforms & LLM frameworks.\n 3. Scale our engineering team\u2014we're hiring! (If you love ML infra, let\u2019s talk!??? )\nWould be great to hear from the HN community! What are your biggest AI infra pain points? Let\u2019s discuss!","title":"Show HN: TrueFoundry raises $19M Series A to scale AI deployment with agents","updated_at":"2025-12-03T16:26:47Z","url":"https://www.truefoundry.com/blog/announcing-our-19m-series-a-scaling-ai-deployment-with-autonomous-agents-on-autopilot"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Hey HN, exciting news! Our RAG framework, Cognita (https://github.com/truefoundry/cognita), born from collaborations with diverse enterprises, is now open-source. Currently, it offers seamless integrations with Qdrant and SingleStore.
In recent weeks, numerous engineers have explored Cognita, providing invaluable insights and feedback. We deeply appreciate your input and encourage ongoing dialogue (share your thoughts in the comments \u2013 let's keep this \u2018open source\u2019).
While RAG is undoubtedly powerful, the process of building a functional application with it can feel overwhelming. From selecting the right AI models to organizing data effectively, there's a lot to navigate. While tools like LangChain and LlamaIndex simplify prototyping, an accessible, ready-to-use open-source RAG template with modular support is still missing. That's where Cognita comes in.
Key benefits of Cognita:
1. Central repository for parsers, loaders, embedders, and retrievers.\n2. User-friendly UI empowers non-technical users to upload documents and engage in Q&A.\n3. Fully API-driven for seamless integration with other systems.
We invite you to explore Cognita and share your feedback as we refine and expand its capabilities. Interested in contributing? Join the journey at https://www.truefoundry.com/cognita-launch."},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Cognita \u2013 open-source RAG framework for modular applications"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://github.com/truefoundry/cognita"}},"_tags":["story","author_supreetgupta","story_40181306","show_hn"],"author":"supreetgupta","children":[40182373,40182485,40183070,40183611,40184216,40185181,40186412,40187284,40187751,40188353,40189399,40190171,40194665,40197110],"created_at":"2024-04-27T16:40:06Z","created_at_i":1714236006,"num_comments":34,"objectID":"40181306","points":142,"story_id":40181306,"story_text":"Hey HN, exciting news! Our RAG framework, Cognita (https://github.com/truefoundry/cognita), born from collaborations with diverse enterprises, is now open-source. Currently, it offers seamless integrations with Qdrant and SingleStore.
In recent weeks, numerous engineers have explored Cognita, providing invaluable insights and feedback. We deeply appreciate your input and encourage ongoing dialogue (share your thoughts in the comments \u2013 let's keep this \u2018open source\u2019).
While RAG is undoubtedly powerful, the process of building a functional application with it can feel overwhelming. From selecting the right AI models to organizing data effectively, there's a lot to navigate. While tools like LangChain and LlamaIndex simplify prototyping, an accessible, ready-to-use open-source RAG template with modular support is still missing. That's where Cognita comes in.
Key benefits of Cognita:
1. Central repository for parsers, loaders, embedders, and retrievers.\n2. User-friendly UI empowers non-technical users to upload documents and engage in Q&A.\n3. Fully API-driven for seamless integration with other systems.
We invite you to explore Cognita and share your feedback as we refine and expand its capabilities. Interested in contributing? Join the journey at https://www.truefoundry.com/cognita-launch.","title":"Show HN: Cognita \u2013 open-source RAG framework for modular applications","updated_at":"2024-09-20T16:56:25Z","url":"https://github.com/truefoundry/cognita"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N\u00d7M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented.
We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future.
The system includes a central MCP registry, support for OAuth2/DCR integration, Virtual MCP Servers for curated toolsets, and a playground for experimenting with tool calls.
Resources -
Architecture Blog \u2013 Covers the N\u00d7M problem, gateway motivation, design choices, auth layers, Virtual MCP Servers, and the overall model.
https://www.truefoundry.com/blog/introducing-truefoundry-mcp...
Tutorial \u2013 Step-by-step guide to writing an MCP server, adding Okta-based OAuth, and integrating it with the Gateway.
https://docs.truefoundry.com/docs/ai-gateway/mcp-server-oaut...
Feedback on gaps and edge cases is welcome.
https://www.truefoundry.com/mcp-gateway"},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: MCP Gateway \u2013 Unifying Access to MCP Servers Without N\u00d7M Integrations"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://www.truefoundry.com/mcp-gateway"}},"_tags":["story","author_supreetgupta","story_46136222","show_hn"],"author":"supreetgupta","children":[46136355,46136708,46145656],"created_at":"2025-12-03T16:14:29Z","created_at_i":1764778469,"num_comments":3,"objectID":"46136222","points":10,"story_id":46136222,"story_text":"Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N\u00d7M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented.
We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future.
The system includes a central MCP registry, support for OAuth2/DCR integration, Virtual MCP Servers for curated toolsets, and a playground for experimenting with tool calls.
Resources -
Architecture Blog \u2013 Covers the N\u00d7M problem, gateway motivation, design choices, auth layers, Virtual MCP Servers, and the overall model.
https://www.truefoundry.com/blog/introducing-truefoundry-mcp...
Tutorial \u2013 Step-by-step guide to writing an MCP server, adding Okta-based OAuth, and integrating it with the Gateway.
https://docs.truefoundry.com/docs/ai-gateway/mcp-server-oaut...
Feedback on gaps and edge cases is welcome.
https://www.truefoundry.com/mcp-gateway","title":"Show HN: MCP Gateway \u2013 Unifying Access to MCP Servers Without N\u00d7M Integrations","updated_at":"2026-03-05T23:06:33Z","url":"https://www.truefoundry.com/mcp-gateway"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"deeptishukla22"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Hi HN, I work at TrueFoundry.
We built Aitori because AI traffic is getting harder for companies to control.
When developers call an LLM API directly, the request can be routed through a gateway. But tools like Claude Desktop, ChatGPT app, claude.ai call the model from the vendor\u2019s backend. There is no endpoint setting you can point to your proxy.
Aitori is an open-source local proxy that runs on the employee\u2019s machine and intercepts traffic to selected AI applications.
It uses a per-device CA, similar to mitmproxy, to inspect model and MCP requests and forward them to a gateway. Traffic to other applications is left untouched.
Once you can see the traffic, it stops being a black box. You can log it, apply policy, route it, or do whatever else you would with AI traffic you control.
It's Apache-2.0, and the forwarding contract is documented so it works with any gateway, not just ours: https://github.com/truefoundry/aitori/
Try it:\n curl -fsSL https://raw.githubusercontent.com/truefoundry/aitori/main/in... | sh\n then\n sudo aitori up --ui
Around all day to answer any questions."},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Aitori, see and govern the AI traffic leaving your machine"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://github.com/truefoundry/aitori/"}},"_tags":["story","author_deeptishukla22","story_49068422","show_hn"],"author":"deeptishukla22","children":[49068460,49068627,49069291],"created_at":"2026-07-27T12:05:23Z","created_at_i":1785153923,"num_comments":2,"objectID":"49068422","points":2,"story_id":49068422,"story_text":"Hi HN, I work at TrueFoundry.
We built Aitori because AI traffic is getting harder for companies to control.
When developers call an LLM API directly, the request can be routed through a gateway. But tools like Claude Desktop, ChatGPT app, claude.ai call the model from the vendor\u2019s backend. There is no endpoint setting you can point to your proxy.
Aitori is an open-source local proxy that runs on the employee\u2019s machine and intercepts traffic to selected AI applications.
It uses a per-device CA, similar to mitmproxy, to inspect model and MCP requests and forward them to a gateway. Traffic to other applications is left untouched.
Once you can see the traffic, it stops being a black box. You can log it, apply policy, route it, or do whatever else you would with AI traffic you control.
It's Apache-2.0, and the forwarding contract is documented so it works with any gateway, not just ours: https://github.com/truefoundry/aitori/
Try it:\n curl -fsSL https://raw.githubusercontent.com/truefoundry/aitori/main/in... | sh\n then\n sudo aitori up --ui
Around all day to answer any questions.","title":"Show HN: Aitori, see and govern the AI traffic leaving your machine","updated_at":"2026-07-27T13:17:46Z","url":"https://github.com/truefoundry/aitori/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"s1lv3rj1nx"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"I'm a software engineer who works with LLMs professionally (Forward Deployed Engineer at TrueFoundry). Over the past year I built up implementations of five LLM architectures from scratch and wrote a book around them.
The progression:
- Ch1: Vanilla encoder-decoder transformer (English to Hindi translation)\n- Ch2: GPT-2 124M from scratch, loads real OpenAI pretrained weights\n- Ch3: Llama 3.2-3B by swapping 4 components of GPT-2 (LayerNorm to RMSNorm, learned PE to RoPE, GELU to SwiGLU, MHA to GQA), loads Meta's pretrained weights\n- Ch4: KV cache, MQA, GQA (inference optimisation)\n- Ch5: DeepSeek MLA (absorption trick, decoupled RoPE), DeepSeekMoE, Multi-Token Prediction, FP8 quantisation
All code is open source: https://github.com/S1LV3RJ1NX/mal-code
The book provides the explanations, derivations, diagrams, and narrative: https://leanpub.com/adventures-with-llms (free sample available)
I wrote it because most resources stop at GPT-2 and I wanted something that covered what's actually in production models today. Happy to answer questions about any of the implementations."},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: A book that builds GPT-2, Llama 3, DeepSeek from scratch in PyTorch"}},"_tags":["story","author_s1lv3rj1nx","story_47779084","show_hn"],"author":"s1lv3rj1nx","children":[47782072],"created_at":"2026-04-15T14:01:34Z","created_at_i":1776261694,"num_comments":1,"objectID":"47779084","points":2,"story_id":47779084,"story_text":"I'm a software engineer who works with LLMs professionally (Forward Deployed Engineer at TrueFoundry). Over the past year I built up implementations of five LLM architectures from scratch and wrote a book around them.
The progression:
- Ch1: Vanilla encoder-decoder transformer (English to Hindi translation)\n- Ch2: GPT-2 124M from scratch, loads real OpenAI pretrained weights\n- Ch3: Llama 3.2-3B by swapping 4 components of GPT-2 (LayerNorm to RMSNorm, learned PE to RoPE, GELU to SwiGLU, MHA to GQA), loads Meta's pretrained weights\n- Ch4: KV cache, MQA, GQA (inference optimisation)\n- Ch5: DeepSeek MLA (absorption trick, decoupled RoPE), DeepSeekMoE, Multi-Token Prediction, FP8 quantisation
All code is open source: https://github.com/S1LV3RJ1NX/mal-code
The book provides the explanations, derivations, diagrams, and narrative: https://leanpub.com/adventures-with-llms (free sample available)
I wrote it because most resources stop at GPT-2 and I wanted something that covered what's actually in production models today. Happy to answer questions about any of the implementations.","title":"Show HN: A book that builds GPT-2, Llama 3, DeepSeek from scratch in PyTorch","updated_at":"2026-04-15T17:13:12Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"Swapnoneel"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"So, I was recently exploring different options for model routing based on task complexity, and realized that it\u2019s absolutely essential that the model router provides an unified MCP gateway as well.
Because it\u2019s as painful as connecting your separate providers to a service. For example, you are using OpenCode and Hermes, and as provider, you have got Groq, OpenRouter and Anthropic, and also a couple of MCPs. So, the hassle comes from connecting all your MCPs and LLM providers to both OpenCode and Hermes separately. Now, you can do it for two, but what if you also use OpenClaw, jcode, or Muse Code? It becomes a nightmare of executing busy chores.
So, a LLM and MCP gateway like Bifrost becomes necessary, which is both free and open-source. Out of all the solutions I tried like Truefoundry or LiteLLM, Bifrost sounded the best one to me. Please share your feedbacks and opinion regarding this in the comments."},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: A model router should also provide a MCP gateway"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://github.com/maximhq/bifrost/"}},"_tags":["story","author_Swapnoneel","story_49212357","show_hn"],"author":"Swapnoneel","children":[49218712],"created_at":"2026-08-07T15:54:14Z","created_at_i":1786118054,"num_comments":0,"objectID":"49212357","points":2,"story_id":49212357,"story_text":"So, I was recently exploring different options for model routing based on task complexity, and realized that it\u2019s absolutely essential that the model router provides an unified MCP gateway as well.
Because it\u2019s as painful as connecting your separate providers to a service. For example, you are using OpenCode and Hermes, and as provider, you have got Groq, OpenRouter and Anthropic, and also a couple of MCPs. So, the hassle comes from connecting all your MCPs and LLM providers to both OpenCode and Hermes separately. Now, you can do it for two, but what if you also use OpenClaw, jcode, or Muse Code? It becomes a nightmare of executing busy chores.
So, a LLM and MCP gateway like Bifrost becomes necessary, which is both free and open-source. Out of all the solutions I tried like Truefoundry or LiteLLM, Bifrost sounded the best one to me. Please share your feedbacks and opinion regarding this in the comments.","title":"Show HN: A model router should also provide a MCP gateway","updated_at":"2026-08-08T03:43:28Z","url":"https://github.com/maximhq/bifrost/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"shubhamagarwal3"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Hey, I'm from TrueFoundry team that open-sourced this. Pi is great but it's solving a different problem than we are.
It's a CLI coding agent that lives in your terminal, built mainly for devs working on a codebase on their own machines.
TrueForge is a runtime for building and running general agents. It comes with a server and web UI, plus an SDK and API. So you can build production agents and run them for yourself or your org, self-hosted behind SSO.
The idea is providing an end-to-end path: build agents in the UI, access them via API, and deploy for your team."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"TrueForge \u2013 The open-source agent harness"},"story_url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://github.com/truefoundry/trueforge"}},"_tags":["comment","author_shubhamagarwal3","story_49378419"],"author":"shubhamagarwal3","comment_text":"Hey, I'm from TrueFoundry team that open-sourced this. Pi is great but it's solving a different problem than we are.
It's a CLI coding agent that lives in your terminal, built mainly for devs working on a codebase on their own machines.
TrueForge is a runtime for building and running general agents. It comes with a server and web UI, plus an SDK and API. So you can build production agents and run them for yourself or your org, self-hosted behind SSO.
The idea is providing an end-to-end path: build agents in the UI, access them via API, and deploy for your team.","created_at":"2026-08-21T09:07:35Z","created_at_i":1787303255,"objectID":"49385612","parent_id":49379391,"story_id":49378419,"story_title":"TrueForge \u2013 The open-source agent harness","story_url":"https://github.com/truefoundry/trueforge","updated_at":"2026-09-18T09:20:02Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"jubilanti"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"> There's no single database with information about all the available AI models. We started Models.dev as a community-contributed project to address this.
There are literally dozens of existing projects that are doing what you are trying to do.
Insert XKCD standards reference here:
https://www.helicone.ai/llm-cost
https://docs.litellm.ai/docs/provider_registration/add_model...
https://artificialanalysis.ai/api-reference
https://github.com/simonw/llm-prices
https://github.com/assistant-ui/modelpedia
https://github.com/pydantic/genai-prices
https://github.com/Portkey-AI/models
https://github.com/truefoundry/models
https://github.com/agentstation/starmap
https://github.com/dcSpark/ai-model-catalog
https://github.com/mitkury/aimodels
https://github.com/nuxdie/ai-pricing"},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Models.dev: open-source database of AI model specs, pricing, and capabilities"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://github.com/anomalyco/models.dev"}},"_tags":["comment","author_jubilanti","story_48241172"],"author":"jubilanti","children":[48241969,48243924,48244121,48246505],"comment_text":"> There's no single database with information about all the available AI models. We started Models.dev as a community-contributed project to address this.
There are literally dozens of existing projects that are doing what you are trying to do.
Insert XKCD standards reference here:
https://www.helicone.ai/llm-cost
https://docs.litellm.ai/docs/provider_registration/add_model...
https://artificialanalysis.ai/api-reference
https://github.com/simonw/llm-prices
https://github.com/assistant-ui/modelpedia
https://github.com/pydantic/genai-prices
https://github.com/Portkey-AI/models
https://github.com/truefoundry/models
https://github.com/agentstation/starmap
https://github.com/dcSpark/ai-model-catalog
https://github.com/mitkury/aimodels
https://github.com/nuxdie/ai-pricing","created_at":"2026-05-22T21:33:20Z","created_at_i":1779485600,"objectID":"48241949","parent_id":48241172,"story_id":48241172,"story_title":"Models.dev: open-source database of AI model specs, pricing, and capabilities","story_url":"https://github.com/anomalyco/models.dev","updated_at":"2026-05-25T10:43:20Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"A bit more context: this Gateway is part of a progression from an LLM Gateway - MCP Gateway - a future Agent Gateway. The intent is to provide a consistent control plane for tool access, authentication, and policies around agent execution. MCP offers a clean interoperability layer, so the Gateway focuses on security, observability, and operational consistency rather than tool-specific logic.
There are areas still evolving (more granular budget/rate controls, extended tool composition inside Virtual MCP Servers, richer audit traces). Input from people who\u2019ve built multi-tool agent systems or worked with MCP at scale would be especially useful.
Refer to our roadmap here - https://www.truefoundry.com/roadmap"},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: MCP Gateway \u2013 Unifying Access to MCP Servers Without N\u00d7M Integrations"},"story_url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://www.truefoundry.com/mcp-gateway"}},"_tags":["comment","author_supreetgupta","story_46136222"],"author":"supreetgupta","comment_text":"A bit more context: this Gateway is part of a progression from an LLM Gateway - MCP Gateway - a future Agent Gateway. The intent is to provide a consistent control plane for tool access, authentication, and policies around agent execution. MCP offers a clean interoperability layer, so the Gateway focuses on security, observability, and operational consistency rather than tool-specific logic.
There are areas still evolving (more granular budget/rate controls, extended tool composition inside Virtual MCP Servers, richer audit traces). Input from people who\u2019ve built multi-tool agent systems or worked with MCP at scale would be especially useful.
Refer to our roadmap here - https://www.truefoundry.com/roadmap","created_at":"2025-12-03T16:47:56Z","created_at_i":1764780476,"objectID":"46136708","parent_id":46136222,"story_id":46136222,"story_title":"Show HN: MCP Gateway \u2013 Unifying Access to MCP Servers Without N\u00d7M Integrations","story_url":"https://www.truefoundry.com/mcp-gateway","updated_at":"2026-03-05T23:06:33Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"valyala"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"VictoriaLogs - https://www.truefoundry.com/blog/victorialogs-vs-loki"},"story_title":{"matchLevel":"none","matchedWords":[],"value":"I can't recommend Grafana anymore"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://henrikgerdes.me/blog/2025-11-grafana-mess/"}},"_tags":["comment","author_valyala","story_45934940"],"author":"valyala","comment_text":"VictoriaLogs - https://www.truefoundry.com/blog/victorialogs-vs-loki","created_at":"2025-11-17T07:52:05Z","created_at_i":1763365925,"objectID":"45951642","parent_id":45935361,"story_id":45934940,"story_title":"I can't recommend Grafana anymore","story_url":"https://henrikgerdes.me/blog/2025-11-grafana-mess/","updated_at":"2026-03-05T23:01:04Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"bharatgel"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"A curated list of awesome Model Context Protocol solutions for for building, finding, hosting, learning, securing, and using MCP offerings. Sharing the current list here :
--- Private Registries
Ready-to-use pluggable MCP server implementations where MCP servers and tools are managed by the organization. They usually come with auth, guardrails, observability and more.
Composio (https://composio.dev) - Skills that evolve for your Agents. More than just integrations, 10,000+ tools that can adapt \u2014 turning automation into intuition.
Docker MCP Catalog (https://hub.docker.com/mcp) - Ready-to-use container images for MCP servers for simple Docker-based deployment.
Glama (https://glama.ai/) - Managed MCP platform: directories, hosted servers, AI gateway, agents/automations, logging/traceability, and public MCP API.
Gumloop (https://www.gumloop.com/mcp) - Workflow automation platform with built-in MCP server integrations. Connects MCP tools to automate workflows and integrate data across services.
Klavis AI (https://www.klavis.ai/) - Managed MCP servers for common AI tool integrations with built-in auth and monitoring.
Make MCP (https://www.make.com/en) - Integration module for connecting MCP servers to Make.com workflows. Enables workflow automations with MCP servers.
mcp.run (https://mcp.run) - One platform for vertical AI across your organization. Instantly deploy MCP servers in the cloud for rapid prototyping or production use.
Pipedream (https://mcp.pipedream.com/) - AI developer toolkit for integrations: add 2,800+ APIs and 10,000+ tools to your assistant.
SuperMachine (https://supermachine.ai/) - One-click hosted MCP servers with thousands of AI agent tools available instantly. Simple, managed setup and integration.
Zapier MCP (https://zapier.com/mcp) - Connect your AI to any app with Zapier MCP. The fastest way to let your AI assistant interact with thousands of apps.
--- Gateways & Proxies
MCP gateways, proxies, and routing solutions for enterprise architectures. Most also provide security features like OAuth, authn/authz, and guardrails.
Arcade.dev (https://www.arcade.dev) - AI Tool-calling Platform that securely connects AI to MCPs, APIs, data, and more. Build assistants that don't just chat \u2013 they get work done.
catie-mcp (https://www.catiemcp.com/) - Context-aware, configurable proxy for routing MCP JSON-RPC requests to appropriate backends based on request content.
FLUJO (https://github.com/mario-andreschak/FLUJO) - MCP hub/inspector with multi-model workflow and chat interface for complex agent workflows using MCP servers and tools.
Lasso MCP Gateway (https://www.lasso.security/) - Protects every interaction with LLMs across your organization \u2014 simple, seamless, secure.
MCP Context Forge (https://github.com/IBM/mcp-context-forge) - Feature-rich MCP gateway, proxy, and registry built on FastAPI - unifies discovery, auth, rate-limiting, virtual servers, and observability.
MCP-connect (https://github.com/EvalsOne/MCP-connect) - Proxy/client to let cloud services call local stdio-based MCP servers over HTTP for easy workflow integration.
MetaMCP - Open source. Proxy and aggregate multiple MCP servers into meta-MCPs, and host as SSE/SHTTP/OpenAPI endpoints with middleware, OAuth, and tool management. Stdio MCP servers hosting supported.
Microsoft MCP Gateway (https://github.com/microsoft/mcp-gateway) - Reverse proxy and management layer for MCP servers with scalable, session-aware routing and lifecycle management on Kubernetes.
Traego (https://traego.ai) - Supercharge your AI workflows with a single endpoint.
TrueFoundry (https://www.truefoundry.com/mcp-gateway) - Enterprise-grade MCP gateway with secure access, RBAC, observability, and dynamic policy enforcement.
Unla (https://github.com/AmoyLab/Unla) - Lightweight gateway that turns existing MCP servers and APIs into MCP servers with zero code changes.
--- Build Tools & Frameworks
Frameworks and SDKs for building custom MCP servers and clients
Dummy MCP (https://dummymcp.com/) - Create prototype MCP servers instantly: define tools and mock responses to test LLM interactions and iterate quickly.
FastAPI MCP (https://github.com/tadata-org/fastapi_mcp) - Expose your FastAPI endpoints as MCP tools with auth.
FastMCP (https://gofastmcp.com/) - The fast, Pythonic way to build MCP servers and clients with comprehensive tooling.
Golf.dev (https://golf.dev/) - Turn your code into spec-compliant MCP servers with zero boilerplate.
Lean MCP (https://leanmcp.com/) - Lightweight toolkit for quickly building MCP\u2011compliant servers without heavy dependencies.
MCPJam Inspector (https://github.com/MCPJam/inspector) - "Postman for MCPs" \u2014 test and debug MCP servers by sending requests and viewing responses.
mcpadapt (https://grll.github.io/mcpadapt/) - Unlock 650+ MCP tools in your favorite agentic framework. Manages and adapts MCP server tools into the appropriate format for each agent framework.
mcp-use (https://github.com/mcp-use/mcp-use) - Open-source toolkit to connect any LLM to any MCP server and build custom MCP agents with tool access.
Naptha AI (https://auto-mcp.com/) - Turn any agents, tools, or orchestrators into an MCP server in seconds; automates hosting and scaling from source or templates.
Tadata (https://tadata.com/) - Convert your OpenAPI spec into MCP servers so your API is accessible to AI agents.
--- Security & Governance
Security, observability, guardrails, identity, and governance for MCP implementations
Invariant Labs (https://invariantlabs.ai/) - Infrastructure and tooling for secure, reliable AI agents, including hosting, compliance, and security layers.
Ithena MCP Governance SDK (https://www.ithena.one/) - End-to-end observability for MCP tools: monitor requests, responses, errors, and performance without code changes.
Pomerium (https://www.pomerium.com/) - Zero Trust access for every identity - humans, services, and AI agents. Every request secured by policy, not perimeter.
Prefactor (https://prefactor.tech/) - Native MCP Identity Layer for Modern SaaS. Secure, authorize, and audit AI agents \u2014 not just users.
SGNL (https://sgnl.ai/) - Policy-based control plane for AI: govern access between agents, MCP servers, and enterprise data using identity and policies.
--- Infrastructure & Deployment\nTools for deploying, scaling, and managing MCP servers in production
Blaxel (https://blaxel.ai/) - Serverless platform for building, deploying, and scaling AI agents with rich observability and GitHub-native workflows.
Cloudflare Agents (https://developers.cloudflare.com/agents/model-context-proto...) - Build and deploy remote MCP servers with built-in authn/authz on Cloudflare.
FastMCP Cloud (https://www.fastmcp.cloud/) - Hosted FastMCP deployment to go from code to production quickly.
Shinzo Labs (https://shinzo.ai/) - Complete observability for MCP servers: anonymous usage analytics, error tracking, and configurable data sanitization; GDPR/CPRA-friendly with self\u2011hosting options.
--- MCP Directories & Marketplaces\nCurated collections and marketplaces of pre-built MCP servers for various integrations
Awesome MCP Servers (https://github.com/wong2/awesome-mcp-servers) - Curated list of MCP servers, tools, and related resources.
Dexter MCP (https://www.dextermcp.net/) - Comprehensive directory for Model Context Protocol servers and AI tools. Discover, compare, and implement the best AI technologies for your workflow.
MCP Market (https://mcpmarket.com) - Directory of awesome MCP servers and clients to connect AI agents with your favorite tools.
MCP SO (https://mcp.so) - Connect the world with MCP. Find awesome MCP servers. Build AI agents quickly.
OpenTools (https://opentools.com/registry) - Public registry of AI tools and MCP servers for integration and deployment. Allows discovery and use of AI and MCP-compatible tools through a searchable registry.
PulseMCP (https://www.pulsemcp.com/) - Browse and discover MCP use cases, servers, clients, and news. Keep up-to-date with the MCP ecosystem.
Smithery (https://smithery.ai/) - Gateway to 5000+ ready-made MCP servers with one-click deployment."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"[dead]"}},"_tags":["comment","author_bharatgel","story_44880517"],"author":"bharatgel","comment_text":"A curated list of awesome Model Context Protocol solutions for for building, finding, hosting, learning, securing, and using MCP offerings. Sharing the current list here :
--- Private Registries
Ready-to-use pluggable MCP server implementations where MCP servers and tools are managed by the organization. They usually come with auth, guardrails, observability and more.
Composio (https://composio.dev) - Skills that evolve for your Agents. More than just integrations, 10,000+ tools that can adapt \u2014 turning automation into intuition.
Docker MCP Catalog (https://hub.docker.com/mcp) - Ready-to-use container images for MCP servers for simple Docker-based deployment.
Glama (https://glama.ai/) - Managed MCP platform: directories, hosted servers, AI gateway, agents/automations, logging/traceability, and public MCP API.
Gumloop (https://www.gumloop.com/mcp) - Workflow automation platform with built-in MCP server integrations. Connects MCP tools to automate workflows and integrate data across services.
Klavis AI (https://www.klavis.ai/) - Managed MCP servers for common AI tool integrations with built-in auth and monitoring.
Make MCP (https://www.make.com/en) - Integration module for connecting MCP servers to Make.com workflows. Enables workflow automations with MCP servers.
mcp.run (https://mcp.run) - One platform for vertical AI across your organization. Instantly deploy MCP servers in the cloud for rapid prototyping or production use.
Pipedream (https://mcp.pipedream.com/) - AI developer toolkit for integrations: add 2,800+ APIs and 10,000+ tools to your assistant.
SuperMachine (https://supermachine.ai/) - One-click hosted MCP servers with thousands of AI agent tools available instantly. Simple, managed setup and integration.
Zapier MCP (https://zapier.com/mcp) - Connect your AI to any app with Zapier MCP. The fastest way to let your AI assistant interact with thousands of apps.
--- Gateways & Proxies
MCP gateways, proxies, and routing solutions for enterprise architectures. Most also provide security features like OAuth, authn/authz, and guardrails.
Arcade.dev (https://www.arcade.dev) - AI Tool-calling Platform that securely connects AI to MCPs, APIs, data, and more. Build assistants that don't just chat \u2013 they get work done.
catie-mcp (https://www.catiemcp.com/) - Context-aware, configurable proxy for routing MCP JSON-RPC requests to appropriate backends based on request content.
FLUJO (https://github.com/mario-andreschak/FLUJO) - MCP hub/inspector with multi-model workflow and chat interface for complex agent workflows using MCP servers and tools.
Lasso MCP Gateway (https://www.lasso.security/) - Protects every interaction with LLMs across your organization \u2014 simple, seamless, secure.
MCP Context Forge (https://github.com/IBM/mcp-context-forge) - Feature-rich MCP gateway, proxy, and registry built on FastAPI - unifies discovery, auth, rate-limiting, virtual servers, and observability.
MCP-connect (https://github.com/EvalsOne/MCP-connect) - Proxy/client to let cloud services call local stdio-based MCP servers over HTTP for easy workflow integration.
MetaMCP - Open source. Proxy and aggregate multiple MCP servers into meta-MCPs, and host as SSE/SHTTP/OpenAPI endpoints with middleware, OAuth, and tool management. Stdio MCP servers hosting supported.
Microsoft MCP Gateway (https://github.com/microsoft/mcp-gateway) - Reverse proxy and management layer for MCP servers with scalable, session-aware routing and lifecycle management on Kubernetes.
Traego (https://traego.ai) - Supercharge your AI workflows with a single endpoint.
TrueFoundry (https://www.truefoundry.com/mcp-gateway) - Enterprise-grade MCP gateway with secure access, RBAC, observability, and dynamic policy enforcement.
Unla (https://github.com/AmoyLab/Unla) - Lightweight gateway that turns existing MCP servers and APIs into MCP servers with zero code changes.
--- Build Tools & Frameworks
Frameworks and SDKs for building custom MCP servers and clients
Dummy MCP (https://dummymcp.com/) - Create prototype MCP servers instantly: define tools and mock responses to test LLM interactions and iterate quickly.
FastAPI MCP (https://github.com/tadata-org/fastapi_mcp) - Expose your FastAPI endpoints as MCP tools with auth.
FastMCP (https://gofastmcp.com/) - The fast, Pythonic way to build MCP servers and clients with comprehensive tooling.
Golf.dev (https://golf.dev/) - Turn your code into spec-compliant MCP servers with zero boilerplate.
Lean MCP (https://leanmcp.com/) - Lightweight toolkit for quickly building MCP\u2011compliant servers without heavy dependencies.
MCPJam Inspector (https://github.com/MCPJam/inspector) - "Postman for MCPs" \u2014 test and debug MCP servers by sending requests and viewing responses.
mcpadapt (https://grll.github.io/mcpadapt/) - Unlock 650+ MCP tools in your favorite agentic framework. Manages and adapts MCP server tools into the appropriate format for each agent framework.
mcp-use (https://github.com/mcp-use/mcp-use) - Open-source toolkit to connect any LLM to any MCP server and build custom MCP agents with tool access.
Naptha AI (https://auto-mcp.com/) - Turn any agents, tools, or orchestrators into an MCP server in seconds; automates hosting and scaling from source or templates.
Tadata (https://tadata.com/) - Convert your OpenAPI spec into MCP servers so your API is accessible to AI agents.
--- Security & Governance
Security, observability, guardrails, identity, and governance for MCP implementations
Invariant Labs (https://invariantlabs.ai/) - Infrastructure and tooling for secure, reliable AI agents, including hosting, compliance, and security layers.
Ithena MCP Governance SDK (https://www.ithena.one/) - End-to-end observability for MCP tools: monitor requests, responses, errors, and performance without code changes.
Pomerium (https://www.pomerium.com/) - Zero Trust access for every identity - humans, services, and AI agents. Every request secured by policy, not perimeter.
Prefactor (https://prefactor.tech/) - Native MCP Identity Layer for Modern SaaS. Secure, authorize, and audit AI agents \u2014 not just users.
SGNL (https://sgnl.ai/) - Policy-based control plane for AI: govern access between agents, MCP servers, and enterprise data using identity and policies.
--- Infrastructure & Deployment\nTools for deploying, scaling, and managing MCP servers in production
Blaxel (https://blaxel.ai/) - Serverless platform for building, deploying, and scaling AI agents with rich observability and GitHub-native workflows.
Cloudflare Agents (https://developers.cloudflare.com/agents/model-context-proto...) - Build and deploy remote MCP servers with built-in authn/authz on Cloudflare.
FastMCP Cloud (https://www.fastmcp.cloud/) - Hosted FastMCP deployment to go from code to production quickly.
Shinzo Labs (https://shinzo.ai/) - Complete observability for MCP servers: anonymous usage analytics, error tracking, and configurable data sanitization; GDPR/CPRA-friendly with self\u2011hosting options.
--- MCP Directories & Marketplaces\nCurated collections and marketplaces of pre-built MCP servers for various integrations
Awesome MCP Servers (https://github.com/wong2/awesome-mcp-servers) - Curated list of MCP servers, tools, and related resources.
Dexter MCP (https://www.dextermcp.net/) - Comprehensive directory for Model Context Protocol servers and AI tools. Discover, compare, and implement the best AI technologies for your workflow.
MCP Market (https://mcpmarket.com) - Directory of awesome MCP servers and clients to connect AI agents with your favorite tools.
MCP SO (https://mcp.so) - Connect the world with MCP. Find awesome MCP servers. Build AI agents quickly.
OpenTools (https://opentools.com/registry) - Public registry of AI tools and MCP servers for integration and deployment. Allows discovery and use of AI and MCP-compatible tools through a searchable registry.
PulseMCP (https://www.pulsemcp.com/) - Browse and discover MCP use cases, servers, clients, and news. Keep up-to-date with the MCP ecosystem.
Smithery (https://smithery.ai/) - Gateway to 5000+ ready-made MCP servers with one-click deployment.","created_at":"2025-08-12T19:05:21Z","created_at_i":1755025521,"objectID":"44880518","parent_id":44880517,"story_id":44880517,"story_title":"[dead]","updated_at":"2026-03-05T22:34:19Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"ramantehlan"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Elasti lets you scale standard Kubernetes HTTP services to zero without adopting Knative, OpenFaaS, or other FaaS platforms.
It works by adding a lightweight proxy and controller that buffer requests during cold starts and trigger scale-up automatically. No changes to your app, no function rewrites, no new abstractions.
Designed for teams that want serverless-style efficiency using plain Kubernetes primitives.
GitHub: https://github.com/truefoundry/elasti"},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Elasti: Lightweight Scale-to-Zero for Existing Kubernetes Services"},"story_url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://github.com/truefoundry/elasti"}},"_tags":["comment","author_ramantehlan","story_44440141"],"author":"ramantehlan","comment_text":"Elasti lets you scale standard Kubernetes HTTP services to zero without adopting Knative, OpenFaaS, or other FaaS platforms.
It works by adding a lightweight proxy and controller that buffer requests during cold starts and trigger scale-up automatically. No changes to your app, no function rewrites, no new abstractions.
Designed for teams that want serverless-style efficiency using plain Kubernetes primitives.
GitHub: https://github.com/truefoundry/elasti","created_at":"2025-07-02T04:01:12Z","created_at_i":1751428872,"objectID":"44440142","parent_id":44440141,"story_id":44440141,"story_title":"Elasti: Lightweight Scale-to-Zero for Existing Kubernetes Services","story_url":"https://github.com/truefoundry/elasti","updated_at":"2025-07-02T04:04:50Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"magaton"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Hello, a very interesting project. Conratulations for putting everything together.\nI have expressed some thoughts in the discussion sections of Cognita github repo:\nhttps://github.com/truefoundry/cognita/discussions/146\nIt would be great if the maintainers could reply."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Cognita \u2013 open-source RAG framework for modular applications"},"story_url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://github.com/truefoundry/cognita"}},"_tags":["comment","author_magaton","story_40181306"],"author":"magaton","children":[40190634],"comment_text":"Hello, a very interesting project. Conratulations for putting everything together.\nI have expressed some thoughts in the discussion sections of Cognita github repo:\nhttps://github.com/truefoundry/cognita/discussions/146\nIt would be great if the maintainers could reply.","created_at":"2024-04-28T11:23:43Z","created_at_i":1714303423,"objectID":"40187751","parent_id":40181306,"story_id":40181306,"story_title":"Show HN: Cognita \u2013 open-source RAG framework for modular applications","story_url":"https://github.com/truefoundry/cognita","updated_at":"2024-09-20T16:56:56Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita"},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Ask HN: Is RAG the Future of LLMs?"}},"_tags":["comment","author_supreetgupta","story_40034972"],"author":"supreetgupta","comment_text":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita","created_at":"2024-04-28T02:51:21Z","created_at_i":1714272681,"objectID":"40185614","parent_id":40034972,"story_id":40034972,"story_title":"Ask HN: Is RAG the Future of LLMs?","updated_at":"2024-09-20T16:56:46Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita"},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Make the Most of Retrieval Augmented Generation"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://vectorize.io/make-the-most-of-retrieval-augmented-generation-rag/"}},"_tags":["comment","author_supreetgupta","story_40133454"],"author":"supreetgupta","comment_text":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita","created_at":"2024-04-28T02:50:25Z","created_at_i":1714272625,"objectID":"40185606","parent_id":40133454,"story_id":40133454,"story_title":"Make the Most of Retrieval Augmented Generation","story_url":"https://vectorize.io/make-the-most-of-retrieval-augmented-generation-rag/","updated_at":"2024-09-20T16:56:46Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita \nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so..."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Serverless RAG to 10x Internal Operations"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://www.chatbees.ai"}},"_tags":["comment","author_supreetgupta","story_40149924"],"author":"supreetgupta","comment_text":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita \nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so...","created_at":"2024-04-28T02:47:23Z","created_at_i":1714272443,"objectID":"40185588","parent_id":40149924,"story_id":40149924,"story_title":"Show HN: Serverless RAG to 10x Internal Operations","story_url":"https://www.chatbees.ai","updated_at":"2024-09-20T16:56:46Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita\nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so..."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Cohere-toolkit: a collection of prebuilt components for RAG applications"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://github.com/cohere-ai/cohere-toolkit"}},"_tags":["comment","author_supreetgupta","story_40157383"],"author":"supreetgupta","comment_text":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita\nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so...","created_at":"2024-04-28T01:16:46Z","created_at_i":1714267006,"objectID":"40185129","parent_id":40157383,"story_id":40157383,"story_title":"Cohere-toolkit: a collection of prebuilt components for RAG applications","story_url":"https://github.com/cohere-ai/cohere-toolkit","updated_at":"2024-09-20T16:56:46Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita\nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so..."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Ask HN: RAG for API Documentation"}},"_tags":["comment","author_supreetgupta","story_40140635"],"author":"supreetgupta","comment_text":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita\nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so...","created_at":"2024-04-28T01:15:30Z","created_at_i":1714266930,"objectID":"40185120","parent_id":40140635,"story_id":40140635,"story_title":"Ask HN: RAG for API Documentation","updated_at":"2024-09-20T16:56:46Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita\nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so..."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Challenges of Scaling RAG Applications"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://myscale.com/blog/challenges-of-scaling-rag-apps/"}},"_tags":["comment","author_supreetgupta","story_40164427"],"author":"supreetgupta","comment_text":"TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Try it out: https://github.com/truefoundry/cognita\nRead the technical blog here: https://www.truefoundry.com/blog/cognita-building-an-open-so...","created_at":"2024-04-28T01:14:43Z","created_at_i":1714266883,"objectID":"40185114","parent_id":40164427,"story_id":40164427,"story_title":"Challenges of Scaling RAG Applications","story_url":"https://myscale.com/blog/challenges-of-scaling-rag-apps/","updated_at":"2024-09-20T16:56:46Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"supreetgupta"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"Thanks for highlighting that! Here\u2019s the GitHub link: https://github.com/truefoundry/cognita"},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Cognita \u2013 open-source RAG framework for modular applications"},"story_url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["truefoundry"],"value":"https://github.com/truefoundry/cognita"}},"_tags":["comment","author_supreetgupta","story_40181306"],"author":"supreetgupta","comment_text":"Thanks for highlighting that! Here\u2019s the GitHub link: https://github.com/truefoundry/cognita","created_at":"2024-04-27T22:08:46Z","created_at_i":1714255726,"objectID":"40184038","parent_id":40182373,"story_id":40181306,"story_title":"Show HN: Cognita \u2013 open-source RAG framework for modular applications","story_url":"https://github.com/truefoundry/cognita","updated_at":"2024-09-20T16:56:41Z"}],"hitsPerPage":20,"nbHits":32,"nbPages":2,"page":0,"params":"query=truefoundry&advancedSyntax=true&analyticsTags=backend","processingTimeMS":21,"processingTimingsMS":{"_request":{"roundTrip":16},"afterFetch":{"format":{"highlighting":2,"total":3},"merge":{"mergeLoop":{"prepareNextHit":12,"total":12},"total":13},"total":13},"fetch":{"query":6,"total":7},"total":21},"query":"truefoundry","serverTimeMS":25}