MCPfinder – An MCP server that finds and installs other MCP servers

What it does

AI-first MCP server discovery across Official Registry, Glama, and Smithery. Inspect trust signals, tools and env vars, then generate install config for Claude, Cursor, Claude Code, Cline, and Windsurf.

MCPfinder is a free, open-source discovery and install layer for AI agents. It helps an assistant search multiple MCP registries, inspect trust signals and environment variables, and generate install-ready JSON for the right client. Model Context Protocol (MCP) is an open standard by Anthropic that lets AI models connect to external tools and data sources. Think of it as USB-C for AI — a universal interface. MCP servers give your AI agent superpowers: access databases, call APIs, manage files, interact with services — all through a standardized protocol. MCPfinder is an MCP server that discovers other MCP servers. The primary user is the AI assistant itself; the human installs it once, then…from mcpfinder.dev

In the maker’s words, at launch

I’ve been building and using agents heavily lately. The Model Context Protocol ecosystem is growing insanely fast, but discovering and configuring new tools is still highly manual. Every time I needed to connect an agent to a new service, I had to browse registries, figure out the transport type, identify required…

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  mcp-use2025 · manufact.com · ▲581

  Hi 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:…

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  Mcp-Agent – Build effective agents with Model Context Protocol2025 · github.com · ▲80

  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…

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  Representing Agents as MCP Servers2025 · github.com · ▲58

  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.…

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  Hyperbrowser MCP Server – Connect AI agents to the web through browsers2025 · github.com · ▲63

  Hi HN! Excited to share our MCP Server at Hyperbrowser - something we’ve been working on for a few days. We think it’s a pretty neat way to connect LLMs and IDEs like Cursor / Windsurf to the internet. Our MCP server exposes seven tools for data collection and browsing: 1. `scrape_webpage` - Extract formatted (markdown, screenshot etc) content from any webpage 2. `crawl_webpages` - Navigate through multiple linked pages and extract LLM-friendly formatted content 3. `extract_structured_data` - Convert messy HTML into structured JSON 4. `search_with_bing` - Query the web and get results…

• OS
  Open-Source MCP Server for Context and AI Tools2025 · ▲43

  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…

• MM
  MCPlexor – MCP multiplexer that cuts agent context usage by 95%Feb 2026 · mcplexor.com · ▲6

  I built MCPlexor to solve a token waste problem I kept running into with MCP-based agents. The Problem: MCP (Model Context Protocol) is great for giving LLMs access to external tools. But if you connect multiple servers (GitHub, Linear, Postgres, Slack), you end up with 40-50k tokens of tool definitions injected into every request – before the agent even does anything. On a 200k context model, that's 25% gone. On smaller models, it's worse. And most runs only use 1-2 tools. The Solution: MCPlexor sits between your agent and your MCP servers. Instead of loading all tool definitions upfront:…

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