Dev tools · alternatives · 2026
24 alternatives to Open-source project to convert FastAPIs to MCP servers
I built a zero-configuration tool for automatically exposing FastAPI endpoints as Model Context Protocol (MCP) tools, open to collabs and contributions!
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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mcp-usefree tier, from $25/mo▲581Hi HN, Luigi here. We maintain mcp-use an open-source TypeScript framework for building MCP servers and MCP Apps: https://github.com/mcp-use/mcp-use MCP is now (finally) stateless so we rewrote mcp-use v2 from scratch for the 2026-07-28 MCP spec revision: https://blog.modelcontextprotocol.io/posts/2026-07-28/ Thanks to the rebuild: - Throughput: +27% → from 8,615 to 10,982 median ops/sec - Cold launch: 2.2x faster → from 151.6 ms to 68.1 ms - Clean install: 82% smaller → from 404.6 MiB to 74.4 MiB Benchmark with methodology here:…
2025 · manufact.com · its alternatives →
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FastMCP 3.0▲205The fast, Pythonic way to build MCP servers and clients
Jan 2026 · gofastmcp.com · its alternatives →
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MCP Builder▲115Instantly create & deploy MCP servers from any API spec
2025 · mcp.ag2.ai · its alternatives →
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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 · its alternatives →
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RapidMCP▲234Convert your REST API into an MCP Server in minutes!
2025 · rapid-mcp.com · its alternatives →
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N8N2MCP▲137Turn your N8N workflow to MCP servers with just 3 clicks
2025 · github.com · its alternatives →
- 8MG
Hey HN, Sagiv from liblab is here. We've been deep in the world of API tooling for years at liblab, primarily focusing on generating SDKs and documentation from OpenAPI specs. Recently, we kept running into a recurring frustration: connecting AI tools to existing APIs is way more complex than it should be. You start with a simple goal – let an LLM talk to your API – and suddenly you're neck-deep in spinning up infrastructure, wrestling with authentication, and writing a ton of custom glue code just to translate natural language into structured API calls. Then you have to maintain it all. To…
2025 · mcp.liblab.com · its alternatives →
- 9OS
Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…
2025 · its alternatives →
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SpecToMCP▲19Generate MCP servers from OpenAPI specification files
2025 · spectomcp.updab.com · its alternatives →
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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 · its alternatives →
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Hey folks, I've been building AI agents that need to talk to various APIs, and I got tired of writing custom integrations for every service. So I built the MCP-OpenAPI Server to solve this problem! It's a simple bridge that lets AI agents discover and use our existing OpenAPI endpoints through the Model Context Protocol. No need to write custom code for each service - just point it at the OpenAPI specs, choose which endpoints to expose, and you're good to go. What makes this different from other MCP servers is that it uses SSE transport instead of stdio, making it work well for multi-tenant…
2025 · github.com · its alternatives →
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TLDR: OpenAPI-MCP is a Dockerized server that dynamically generates Model Context Protocol (MCP) tool definitions directly from your Swagger/OpenAPI documentation. It allows your AI agent to seamlessly access any API without additional coding, streamlining development and eliminating repetitive manual setup. For more details, code updates-----: GitHub: ckanthony/openapi-mcp Docker Hub: ckanthony/openapi-mcp
2025 · github.com · its alternatives →
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I'm relatively new to Go, but recently got interested in how MCP servers work. I started thinking about what the architecture of such a project might look like, and decided to build a minimalist version as an experiment. I based it on my past experience writing regular REST API servers and figured it might be useful or interesting to others as well.
2025 · github.com · its alternatives →
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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 · its alternatives →
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An ultra-fast, single-binary MCP server written in Rust as a lightweight alternative to Node.js/Python. - StamManif/mcp-stama
Aug 2026 · github.com · its alternatives →
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Got tired of every MCP example being overly verbose, or needing Docker or Mac-only scripts, so I threw together MCP-123. Point it at a tools.py, run `server.run_server(...)`, and the client auto-discovers/calls functions with OpenAI. I hope this is useful to you all.
2025 · github.com · its alternatives →
- 19TA
Hi HN! We built Zalor. It turns an OpenAPI spec into an MCP server, so you can make your APIs callable by Claude or ChatGPT without writing any code. Here's a list of specs you can try: https://github.com/ZalorAI/test-data/tree/main/openapi, but feel free to use your own. For background, MCP is a protocol that standardizes how you connect tools to AI assistants. We're both engineers at large software companies, and when we worked on MCP integrations we saw how long setup took and how often the spec was changing. So we built a platform to handle the MCP…
Dec 2025 · mcp.zalor.ai · its alternatives →
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Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
2025 · github.com · its alternatives →
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One MCP▲13Hey HN, I’ve been experimenting with how LLMs can dynamically use large sets of tools without needing to preload them all into context - and built one-mcp to explore that idea. one-mcp is an open source MCP server built with FastAPI that acts as a semantic index + dynamic loader for API tools. Instead of hardcoding or embedding every tool spec in an LLM session (which quickly blows up context size and costs), one-mcp lets the model search, load, and execute tools on demand — using embeddings and natural language queries. What it does: - Semantic Search for Tools: Query your API catalog with…
2025 · github.com · its alternatives →
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Admittedly I work on this, but I anthropic's decision to finally embrace http, auth (at least a little), and other RFCs that are coming out is just great. With OpenAI behind it too, this ecosystem will be built around projects like this. Not saying it's MCP or not, but it'll be one of them
2025 · twitter.com · its alternatives →
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MCPAGENTSEEK▲14Global search engine for model context protocol tools
2025 · mcpagentseek.com · its alternatives →
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Parse video game save files, serve structured game state to AI assistants via MCP - joshsymonds/savecraft.gg
Mar 2026 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →