"WeChat" matching MCP servers:

Enables DeepSeek Harness to run bounded archive operations—diagnose, status, sync, and verify—against a local macOS chat database with integrity and privacy protections.

An MCP server for sending and receiving WeChat messages, built on Tencent's iLink bot protocol.

Enables AI agents to control WeChat through MCP protocol, including sending messages, managing contacts, and searching messages.

An MCP server that lets an LLM read and drive the macOS WeChat client through the Accessibility API, without reverse-engineering or injected code. It supports listing chats, opening conversations, reading messages, sending actions, and saving media locally.

Automates WeChat on macOS using Accessibility APIs and screen capture, focusing on Excel-driven contact requests, add-friend flows, and friend-request status checks for local outreach workflows.

Enables MCP clients to control the Windows WeChat desktop app, including reading conversations, sending messages, searching contacts, and monitoring new messages via UI automation.

MCP server for pushing scheduled or triggered messages to personal WeChat via ClawBot, using WorkBuddy connector and WeChat iLink API.

A read-only MCP server that enables searching and extracting to-dos from local macOS WeChat chat databases. It decrypts and queries local WeChat data without sending messages or modifying databases.

Enables AI clients to observe WeChat conversations on macOS via local screen capture and Apple Vision OCR, and to preview draft replies without sending messages.

Enables Claude Code to read encrypted WeChat chat history from local database, search messages, view sessions and contacts.

Exposes Windows WeChat desktop client automation as MCP tools, letting AI agents check connection status, list chats, read buffered messages, and send text or files to explicitly specified contacts or groups. Includes safety controls such as target disambiguation, file directory whitelists, optional send confirmation, and operation auditing.

Enables users to retrieve GitLab commit records and automatically generate daily work reports that can be sent to WeChat Work groups. Supports querying commits by date and user, with seamless enterprise messaging integration.

MCP server for reading local WeChat data, enabling AI assistants to query chat history, contacts, sessions, and more via MCP tools.

Enables chatting with an existing OpenAI dot from WeChat by bridging incoming text, images, and files to the dot and sending its replies back to the same conversation.

An unofficial experimental local MCP server that lets AI clients work with an already logged-in Windows Weixin desktop client, providing bounded conversation and message reads, group and message search, polling of up to 16 selected chats, guarded text and attachment submission, and image/file viewing handoffs. It also exposes hybrid Computer Use prompts for native mention handoffs, while remeasuring the window, DPI, and target controls on each action and failing closed when evidence is insufficient.

A production-oriented MCP server that exposes task-level WeChat Desktop automation to AI clients, enabling status checks, message fetching/reply, contact addition, and Moment publishing on macOS via accessibility automation.

Enables connecting a user's own WeChat to MCP-capable AI assistants for owner-only private messaging and media exchange, including receiving text, images, files, and upstream voice transcriptions, and sending replies, images, or files.

A WeChat robot server based on the Model Context Protocol that enables AI agents to send and receive messages and manage typing status. It provides tools for QR code login, long-polling message retrieval, and persistent state management across various MCP clients.

MCP server that lets AI agents manage WeChat Work customer relations via a self-hosted gateway, supporting contact/tag/content queries, group messaging previews and creation, and moment SOP rules with confirm-before-send safety.

Enables automation of WeChat on macOS through the Accessibility API, allowing LLMs to fetch recent messages from contacts and send replies based on conversation history.