Alternatives
Products that do what MCP Server with HTTP support instead of stdio/sse does
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
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- 2MA
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
- 3AS
I started this project because I believe MCP has the potential to transform how AI models interact with external resources, but the ecosystem is still very fragmented. There's no central place to discover and compare all the server implementations available, which makes adoption and experimentation harder for developers. I initially built the GitHub repo awesome-mcp-servers (https://github.com/punkpeye/awesome-mcp-servers/), and it's been amazing to see the community contribute to it. Now, I'm taking it further with a directory that automates many tasks—introspecting…
2024 · glama.ai
- 4RA
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
- 5OS
Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge.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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- 8AM
2025 · github.com
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- 13CD
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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Give AI agents access to real-time data across 200+ apps
May 2026 · apideck.com
- 15CR
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
- 16KA
Hi HN, we are excited to show you Klavis AI. It is an open source project and we provide hosted versions with API access as well. (Website: https://www.klavis.ai/, Github repo: https://github.com/Klavis-AI/klavis) We're addressing a couple of key problems with using MCPs. First, many available MCP servers lack native or used-based authentications, creating security vulnerabilities and adding complexity during development. Second, many MCP servers are personal projects, not designed for the reliability needed in production. Connecting to these servers…
2025 · github.com
- 17RM
We’ve open-sourced the Robot MCP Server, a tool that lets large language models (LLMs) talk directly to robots running ROS1 or ROS2. What it does - Connects any LLM to existing ROS robots via the Model Context Protocol (MCP) - Natural language → ROS topics, services, and actions (And the ability to read any of them back) - Works without changing robot source code Why it matters - Makes robots accessible from natural language interfaces - Opens the door to rapid prototyping of AI-robot applications - We are trying to create a common interface for safe AI ↔ robot communication This is too big…
Sep 2025 · github.com
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- 19MG
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
- 20AL
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
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More than a decade ago, I adopted the self-imposed rule, if I answer a question more than once, the third time I need to be able to answer with a URL. Today, I published one very large URL - a book distilling what I learned from helping people work remotely at GitHub, and I wanted to rethink my rule for the age of AI. What if, instead of a URL, I could create an interactive experience that could tailor the guidance to your particular situation? What I ended up building was an Open and Async Advisor MCP server. To install (in claude or any other AI): > claude mcp add open-async -- npx -y…
Jul 2026 · github.com
- 22MS
2025 · github.com
- 23FA
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
- 24NT
Today we're releasing Nanobot an open-source framework for building AI agents on top of the Model Context Protocol (MCP). MCP servers are a great way to expose structured tools, but they’re usually just that—collections of functions. Nanobot makes it simple to wrap any MCP server with reasoning, a system prompt, and orchestration so it behaves like a real agent. Even better, Nanobot fully supports MCP-UI, so agents can pass rich interactive components (forms, dashboards, even mini-apps) directly into chat. A simple example: if you had a Blackjack MCP server with tools like deal, bet, and…
Sep 2025 · nanobot.ai
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