Alternatives
Products that do what MCP-Bridge does
OpenAPI to hosted MCP endpoint + config registry + bundles
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2025 · github.com
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2025 · github.com
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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
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Zero-dep CLI: one MCP config synced to every agent. A 255-tool listing costs 581 tokens, not 71,929 - schemas never enter context. - activeing123/mcptoon
26d ago · github.com
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I built a zero-configuration tool for automatically exposing FastAPI endpoints as Model Context Protocol (MCP) tools, open to collabs and contributions!
2025 · github.com
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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
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Working in IT at a company with a change management process? How are you handling MCPs? Not at all? With very expensive tools not up to the task? How about just making it fit into your current setup! We needed to build this for inxm.ai, and realised this was the perfect time to give back to the community. Enterprise MCP Bridge is Open Source and solves Auth, Multi User, and REST apis by wrapping your existing MCPs.
2025 · blog.inxm.ai
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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
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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
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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
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Jul 2026 · github.com
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Jan 2026 · github.com
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