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Convert your REST API into an MCP Server in minutes!

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    Instantly create & deploy MCP servers from any API spec

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    The fast, Pythonic way to build MCP servers and clients

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  9. 9OS

    I built a zero-configuration tool for automatically exposing FastAPI endpoints as Model Context Protocol (MCP) tools, open to collabs and contributions!

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

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    Turn any REST APIs into a governed MCP server

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  18. 18CU

    Hi everyone, I built cli-use, a small Python tool that turns any MCP server into a native CLI. The idea is simple: HTTP has curl, Docker has docker, Kubernetes has kubectl — MCP should have a shell-native client too. Why I made it: MCP is useful, but using it through agents has overhead: every session pays schema discovery cost every call carries JSON-RPC framing responses are often verbose JSON when the useful output is just a line or two cli-use converts that into a terse CLI so tools can be called like normal shell commands. Example: pip install cli-use cli-use add fs /tmp cli-use fs…

    Apr 2026

  19. 19FA

    Hi HN -- Since Anthropic announced the Model Context Protocol (MCP) last week [1], I've been excited about giving Claude new capabilities through my custom servers. But while MCP is powerful, implementing the protocol correctly requires a lot of low-level boilerplate code. I found myself wanting something like FastAPI - a high-level framework that would let me focus on building features, not servers. After some hacking, I'm sharing FastMCP: a Pythonic framework for building MCP servers. FastMCP uses decorators to transform normal functions into MCP tools, resources, templates, and prompts,…

    2024 · github.com

  20. 20FM

    I built FastAPI-MCP as an open-source library, and recently had to completely refactor it, abandoning FastMCP wrappers in favor of the low-level MCP SDK. The new version gives more control over which endpoints are exposed, supports complex request bodies, and allows flexible routing options. I wrote about the technical journey and lessons learned here: https://medium.com/@miki_45906/advanced-mcps-in-python-how-t... Looking for feedback and contributors who are interested in MCPs!

    2025 · github.com

  21. 21OP

    Hello HN, Pietro here! I've been really excited to see the recent buzz around MCP and all the cool things people are building with it. Though, the fact that you can use it only through desktop apps really seemed wrong and prevented me for trying most examples, so I wrote a simple client, then I wrapped into some class, and I ended up creating a python package that abstracts some of the async uglyness. You need: * one of those MCPconfig JSONs * 6 lines of code and you can have an agent use the MCP tools from python. The structure is simple: an MCP client creates and manages the connection and…

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  22. 22MS

    Hey, I'm Nick from Nutrient, I want to share our newly released MCP Server that enables document workflows using natural language — things like redacting, merging, signing, converting formats, or extracting data. While many MCP servers have traditionally been developer-focused, we recognized that the technology could be highly effective in promoting the adoption of tools that are often hidden from end-user interfaces. We’re really interested to see if this side of the protocol could continue to mature. One thing we struggled with was the inability to receive documents from the client (no…

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  23. 23MT

    Recently I was trying to use an MCP server to pull data from a service, but hit a limitation: the MCP didn't expose the data I needed, even though the service's REST API supported it. So I wrote a quick CLI wrapper around the API. Worked great, except Claude Code had no structured way to know what my CLI does or how to call it. For `gh` or `curl` the model can learn from the extensive training data, but for a tool I just wrote, it was stabbing in the dark. MCP solves this discovery problem, but it does it by rebuilding tool interaction from scratch: server processes, JSON-RPC transport,…

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