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Build your own Codex with 1000s MCP tools, use anywhere

  1. 1MA

    Hey HN, I spent my xmas break building an agent framework called mcp-agent [1](https://github.com/lastmile-ai/mcp-agent) for Model Context Protocol [2]. It makes it easy to build AI apps with MCP servers, and implements every pattern from the popular Building Effective Agents blog [3] as well as OpenAI’s Swarm [4]. I’m sharing it early to get community feedback on where to take it from here, and to ask for contributions. For those who aren’t familiar with MCP, I think of it as a standardized interface to let AI communicate with software via tool calls, resources and…

    2025 · github.com

  2. 2
    mcp-use581

    Open source SDK and infra for MCP servers & agents

    2025

  3. 3

    Create your custom MCP-Server in seconds

    2025

  4. 4

    Vibe-code MCP-ready tools for any AI Agent

    2025

  5. 5
    Strata652

    One MCP server for AI agents to handle thousands of tools

    Sep 2025 · klavis.ai

  6. 6
    AutoMCP150

    Easily deploy your existing AI agent projects as MCP servers

    2025

  7. 7

    5000+ MCP servers AI tools, 1 line of code

    2025

  8. 8

    Turn any API into an MCP server for AI agents

    Jun 2026 · apitomcp.ai

  9. 9
    MCPCore80

    Build AI-powered MCP servers in the cloud

    Mar 2026 · mcpcore.io

  10. 10

    The fast, Pythonic way to build MCP servers and clients

    Jan 2026 · gofastmcp.com

  11. 11CR

    Hey HN, I built pg-mcp, a Model Context Protocol (MCP) server for PostgreSQL that provides structured schema inspection and query execution for LLMs and agents. It's multi-tenant and runs over HTTP/SSE (not stdio) Features - Supports multiple database connections from multiple agents - Schema Introspection: Returns table structures, types, indexes and constraints; enriched with descriptions from pg_catalog. (for well documented databases) - Read-Only Queries: Controlled execution of queries via MCP. - EXPLAIN Tool: Helps smart agents optimize queries before execution. - Extension…

    2025 · github.com

  12. 12

    easily run MCP (model context protocol) servers in the cloud

    2025

  13. 13

    Build integration tools for MCPs & agents in minutes

    Sep 2025

  14. 14RA

    Hey HN! A few months ago we shared mcp-agent (https://github.com/lastmile-ai/mcp-agent) [1][2], a lightweight framework that implements every agent pattern from Anthropic’s Building Effective Agents blog [3] and handles MCP server/client management seamlessly. Our core bet is that connecting LLMs to tools, resources, and external systems will soon be MCP-native by default. Today we're launching a significant update: Agents as MCP servers. Currently "agentic" behavior exists only on the MCP client side – clients like Claude or Cursor use MCP servers to solve tasks.…

    2025 · github.com

  15. 15MS

    2025 · github.com

  16. 16AM
  17. 17

    The fastest way to connect your data with your AI Tools.

    12d ago · mcp-builder.ai

  18. 18AL

    Most of the MCP servers that I’ve seen are tools implemented in standalone projects. To onboard more tools (especially agents and multi-agent workflows) to MCP, I’ve been thinking it’s important to allow AI engineers to continue to prototype in their existing agent frameworks and deploy with minimal conversion when ready. We created the automcp library, which you can add as a dependency to existing projects (CrewAI, LangGraph, Llama Index, OpenAI Agents SDK, Pydantic AI, mcp-agent currently supported but more coming soon). You just need to run a CLI command to create a run_mcp.py file, make…

    2025 · github.com

  19. 19MU
  20. 20

    Build tool-calling agents in 4 lines of code

    2025

  21. 21

    Connect any API to any AI agent

    May 2026 · mcp-bridge.ai

  22. 22
    N8N2MCP137

    Turn your N8N workflow to MCP servers with just 3 clicks

    2025

  23. 23

    Build and control voice AI agents via MCP

    Apr 2026 · sigmamind.ai

  24. 24MS

    Hi HN! I built a custom MCP (Model Context Protocol) server that connects Blender to LLMs like ChatGPT, Claude, and any other llm supporting tool calling and mcps, enabling the AI to understand and control 3D scenes using natural language. You can describe an entire environment like: > “Create a small village with 5 huts arranged around a central bonfire, add a river flowing on the left, place a wooden bridge across it, and scatter trees randomly.” And the system parses that, reasons about the scene, and builds it inside Blender — no manual modeling or scripting needed. What it can do: -…

    2025 · blender-mcp-psi.vercel.app

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