LIFE
LIFE — Persistent identity architecture for AI agents. 16 MCP servers: drives, heart, memory, patterns, journal, genesis, garden, vision, voice, and…
Find MCP servers that connect AI assistants to useful tools and data. Explore what each server does, its setup and its documentation.
2781 servers · Page 191 of 232
LIFE — Persistent identity architecture for AI agents. 16 MCP servers: drives, heart, memory, patterns, journal, genesis, garden, vision, voice, and…
MCP EU AI Act Compliance Scanner - Open source tool to detect EU AI Act violations in codebases.
Active development continues at ScopeBlind/scopeblind-gateway. - Security gateway for MCP servers.
MCP server for bidirectional AI agent collaboration — 5 tools for spawning and communicating with any agent CLI.
Single-binary Go MCP server that wraps whatsmeow to expose a personal WhatsApp account as 42 MCP tools (messaging, groups, polls, media, privacy).
# Browserbase MCP Server  [The Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) is an open protocol that enables seamless integration between LLM applications and external data…
SAGE — Save AI coding tokens by compressing terminal output, keeping raw logs local, and tracking real savings.
Telegram for AI agents -- messages, chats, media, and contacts across both bot and full user-account modes. 7 tools, with
Booking.com MCP server by HasData: search stays and read full property details, as JSON. 2 tools, with
container-use Containerized environments for coding agents. (📦🤖) (📦🤖) (📦🤖) **Container Use** lets coding agents do their work in parallel environments without getting in your…
MCP server for Facebook: a public page or profile by handle with likes, followers, contact details and the post feed with reactions. 1 tools…
Indeed MCP server by HasData: search job listings and read full postings, as JSON. 2 tools, with
An MCP server exposes tools or data through the Model Context Protocol so a compatible AI client can use them. Each project has its own installation, authentication and permission requirements.
Open a server’s page for its getting-started notes, compatibility and sources, then follow the original project’s documentation for your AI client.
Entries link to the original documentation. Check access requirements, costs and maintenance there before installing, and grant a server only the access it needs.