MCP Documentation Search Server

Created By
PicardRaphaela year ago
🔍 FastMCP-powered documentation search engine that provides unified access to multiple framework docs (Next.js, Tailwind, Framer Motion, etc.) with intelligent name resolution and async processing.
Overview

What is MCP Documentation Search Server?

MCP Documentation Search Server is a powerful documentation search engine built with FastMCP, enabling AI systems to intelligently search across multiple popular framework and library documentations.

How to use MCP Documentation Search Server?

To use the server, clone the repository, set up a virtual environment, install dependencies, and run the server. You can then use the provided API to search documentation for various libraries.

Key features of MCP Documentation Search Server?

  • Multi-library support for frameworks like Next.js, Tailwind CSS, and Framer Motion.
  • Intelligent search with smart name resolution and DuckDuckGo-powered results.
  • Asynchronous processing for efficient web request handling.
  • Robust error handling for network timeouts and invalid inputs.

Use cases of MCP Documentation Search Server?

  1. Quickly finding documentation for specific libraries.
  2. Assisting developers in retrieving relevant information from multiple sources.
  3. Enhancing AI systems with unified access to documentation.

FAQ from MCP Documentation Search Server?

  • What libraries are supported?

The server supports multiple libraries including LangChain, Next.js, Tailwind CSS, and more.

  • Is it easy to set up?

Yes! Follow the quick start guide in the documentation to set it up easily.

  • Can I contribute to the project?

Absolutely! Contributions are welcome, and you can find guidelines in the repository.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
PicardRaphael
Star
0
Language
Python
License
-

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

20 hours ago
Gpt Scrambler

2 days ago