MCP Servers and Tools I Use

Created By
ChenBingWei1201a year ago
A documentation of MCP servers and tools I use with Claude
Overview

What is MCP Servers and Tools I Use?

This project documents the Model Context Protocol (MCP) servers and tools that facilitate AI assistants like Claude in interacting with external systems and data sources.

How to use MCP Servers and Tools?

Users can install the various MCP servers using the provided installation commands and configure them according to their needs. Each server has its own repository for detailed instructions.

Key features of MCP Servers and Tools?

  • Desktop Commander: Terminal control, file system search, and editing capabilities.
  • Tavily MCP: AI-powered web search and content extraction.
  • GitHub MCP: Interaction with GitHub repositories, issues, and pull requests.
  • Memory MCP: Knowledge graph-based memory management.

Use cases of MCP Servers and Tools?

  1. Automating terminal commands with AI assistance.
  2. Conducting comprehensive web searches and extracting relevant content.
  3. Managing GitHub repositories and collaborating on code.
  4. Maintaining contextual information through a knowledge graph.

FAQ from MCP Servers and Tools?

  • What is the purpose of MCP?

MCP enables AI assistants to interact with various external systems, enhancing their capabilities.

  • Are these tools free to use?

Yes, the tools are open-source and can be used freely as per their respective licenses.

  • How do I install the MCP servers?

Each server has specific installation commands provided in their documentation.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
ChenBingWei1201
Star
0
Language
-
License
MIT license

Recommend Servers

View All
Voyei

2 hours ago
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)

a day ago