MCP 服务器

MCP server for the Telegram Bot API. Lets AI agents send messages, deliver files and photos, and read updates from chats and channels through a bot, enabling notifications and conversational workflows from AI-powered tools.

Provides access to the Slack API through the Model Context Protocol. Enables AI agents to read and send messages, manage channels, search conversation history, and interact with Slack workspaces. Supports listing channels, reading threads, posting messages, and adding reactions programmatically. Originally maintained by Anthropic, now maintained by Zencoder.

A Model Context Protocol server that enables AI agents to interact with Discord through a bot. Agents can send and read messages in channels, list servers and channels, and manage basic server interactions while keeping the user in control. Useful for community automation, notifications, and conversational workflows on Discord.

Community MCP server that connects a personal WhatsApp account to AI assistants. Using the WhatsApp multi-device web API, it lets agents search and read your messages and contacts and send messages, including media. Messages are stored locally in SQLite and only shared with the model when the agent accesses them through tools, keeping data on your machine.

Official OpenAI MCP server for integrating GPT models, DALL-E, and Whisper into agentic workflows. Provides tools for chat completion, image generation, audio transcription, and embeddings through the Model Context Protocol. Supports function calling, structured outputs, and streaming responses.

Official Atlassian Rovo MCP Server — a cloud-based bridge between Atlassian Cloud and any MCP-compatible AI tool. Enables AI agents to search, summarize, create, and update Jira issues, Confluence pages, and Compass components in real-time. Uses OAuth 2.1 or API token authentication, respects existing user permissions, and supports remote HTTP-streaming as well as local stdio via the mcp-remote proxy. Works with Claude, GitHub Copilot, Gemini CLI, VS Code, Cursor, and ChatGPT.

A Model Context Protocol server for Google Drive that lets AI assistants list, search, and read files stored in Drive, with automatic export of Google Docs, Sheets, Slides, and Drawings to readable formats. Authenticates via OAuth 2.0 and exposes Drive files as MCP resources so agents can ground their answers in your documents without copying data into chat first.

Pinecone's official MCP server connects AI assistants to Pinecone vector databases for retrieval-augmented generation (RAG) workflows. Lets agents create and configure indexes, upsert and embed documents, and run semantic searches over vector data — all from natural language, without leaving the editor or chat.