mcp
by tunjiadeshina
Overview
Provides a collection of reference implementations for the Model Context Protocol (MCP), enabling Large Language Models (LLMs) with secure, controlled access to external tools and data sources like web content, filesystems, Git repositories, persistent memory, and time utilities.
Installation
npx @modelcontextprotocol/server-everythingEnvironment Variables
- MEMORY_FILE_PATH
- DISABLE_THOUGHT_LOGGING
- PORT
Security Notes
The 'filesystem' server implements robust path validation (symlink resolution, path traversal prevention, atomic writes) which is highly commendable. However, the 'git' server lacks explicit path validation for `repo_path` and `files` arguments, making it a critical security risk where an LLM could be directed to operate on arbitrary paths or repositories on the host system. The 'fetch' server introduces network access capabilities, including the option to ignore `robots.txt`, which poses a risk if misused or misconfigured. The 'memory' server allows `MEMORY_FILE_PATH` to be configured via an environment variable, which could lead to writes to arbitrary locations if set to an unsafe path. The 'everything' server, while a demo, exposes environment variables and network transports, requiring careful deployment. Overall, critical security omissions in some core tools significantly lower the score.
Similar Servers
mcpo
Exposes Model Context Protocol (MCP) tools as OpenAPI-compatible HTTP servers.
awesome-remote-mcp-servers
A curated directory for developers to discover, evaluate, and integrate high-quality, official remote Model Context Protocol (MCP) servers into their AI applications and LLM clients.
mcp-openapi-server
A Model Context Protocol (MCP) server that exposes OpenAPI endpoints as MCP tools, along with optional support for MCP prompts and resources, enabling Large Language Models to interact with REST APIs.
mcp-servers
A curated collection of Model Context Protocol (MCP) server configurations to integrate various developer tools and services with AI agents.