Alternatives
Products that do what Cloud-Deployable Bridge Between OpenAPI Endpoints and MCP does
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…
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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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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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Hey HN, OpenAI released the Agents SDK yesterday, which is great because of its simplicity. I just added MCP support for it, which is currently available as a fork here: https://github.com/lastmile-ai/openai-agents-mcp (and on pypi as the openai-agents-mcp package). You can specify the names of MCP servers to give an Agent access to by setting its `mcp_servers` property. The Agent will then automatically aggregate tools from the MCP servers, as well as any `tools` specified, and create a single extended list of tools. This means you can seamlessly use MCP servers, local…
2025
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Hello HN! Earlier this year, we shared mcp-agent (https://github.com/lastmile-ai/mcp-agent) [1][2], a lightweight framework for building agents with MCP. Since then we have tried to push the protocol to the limits, including hosting agents as long-running tools on MCP [3], and seen other creative approaches surface (mcp-ui, chatgpt apps sdk). Today, we are launching mcp-c – a cloud platform designed for hosting any kind of MCP server, including agents, ChatGPT apps, etc. We are in open beta and free to use, and would love your feedback. Here are some key choices we made:…
Oct 2025 · docs.mcp-agent.com
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Hey HN! I’m Gui from deco (decocms.com). We’ve been using this tool internally as the foundation for a few customer AI platforms, and today we’re open-sourcing it as MCP Mesh. MCP is quickly becoming the standard for agentic systems, but… once you go past a couple servers it turns into the same problems for every team: - M×N config sprawl (every client wired to every server, each with its own JSON + ports + retries) - Token + tool bloat (dumping tool definitions into every prompt doesn’t scale) - Credentials + blast radius (tokens scattered across clients, hard to audit, hard to revoke) - No…
Dec 2025 · github.com
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