WhatsApp MCP Server
Allows AI assistants to manage WhatsApp, including listing chats, searching contacts, sending text messages and files, downloading media, transcribing voice notes, and syncing contacts.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@WhatsApp MCP Serversend a message to John Doe saying 'See you at 5pm'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
WhatsApp MCP Server
A Model Context Protocol (MCP) server that connects to WhatsApp via Baileys, providing AI with the ability to manage WhatsApp. This is a security-hardened fork of karlfoster/whatsapp-mcp-2.0.
⚠️ WARNING
This project uses the UNOFFICIAL WhatsApp Web API (Baileys). WhatsApp may ban accounts using unofficial clients. USE A DEDICATED BURNER NUMBER — never use your personal number. The authors take no responsibility for account bans or any other consequences of using this software.
Related MCP server: WSAPI WhatsApp MCP Server
What This Is
This is a fork of karlfoster/whatsapp-mcp-2.0 with significant security hardening and operational improvements. It allows an AI assistant (like Claude) to:
List and search chats, contacts, and messages.
Send text messages and files (images, videos, documents, audio).
Download media from received messages.
Transcribe voice notes via Whisper-compatible APIs.
Sync phone contacts from VCF files.
Setup
Clone the repository:
git clone <repo-url> cd whatsapp-mcpInstall dependencies:
npm ciConfigure environment variables: Create a
.envfile or set them in your MCP client configuration (see below).Run the server:
npm run devScan the QR code: On first run, a QR code will appear in your terminal. Scan it with WhatsApp on your phone: WhatsApp > Settings > Linked Devices > Link a Device
Environment Variables
Variable | Default | Description |
|
| Directory for outbound file sends. |
|
| Max file size for |
|
| Directory for downloaded media. |
|
| Base directory for VCF imports. |
| (none) | Whisper API endpoint for transcription. |
| (none) | API key for Whisper. |
|
| Model name for transcription. |
|
| Silence before zombie connection detection. |
|
| Consecutive failures before reconnect. |
|
| Minimum delay between sends. |
|
| Random jitter added to send delay. |
|
| Max reconnect attempts before giving up. |
Storage Locations
auth_info/: WhatsApp authentication credentials (DO NOT commit).data/: SQLite database containing messages, chats, and contacts.store/: Baileys message store and.whatsapp.lockfile.uploads/: Files to send (only files in this directory can be sent viasend_file).downloads/: Downloaded media files.contacts/: VCF files for contact import.
Running Tests
This project uses Vitest for testing.
# Run all tests
npx vitest run
# Run tests with coverage
npx vitest run --coverageKnown Limitations
No FTS5: SQLite full-text search is not used; substring search (
LIKE) is used instead.No Read Receipts: The server does not send read receipts.
No Reactions: Message reactions are not supported.
No Stories: WhatsApp Stories/Status updates are not accessible.
Security Changes (What changed from upstream)
Path Traversal Protection: Strict containment checks for
send_fileanddownload_mediausing resolved paths.SSRF Validation:
WHISPER_API_URLis validated to prevent SSRF attacks (rejects localhost and private IP ranges).Atomic Lock File: Prevents multiple instances from connecting to the same WhatsApp account simultaneously.
Strict Filename Sanitization: All filenames are sanitized to prevent injection and traversal.
Bounded Memory Caches: Prevents unbounded memory growth in Baileys message retry and device tracking.
Pre-key Pruning: Automatically prunes old pre-keys to prevent disk bloat.
Removed
reply_spam: Removed the UAE-specific spam reply tool for better general-purpose use.Streamed Uploads:
send_fileuses streams instead of loading full files into memory.
Available Tools
list_chats: List chats sorted by last activity.get_chat: Get chat details with recent messages.list_messages: Get messages from a chat.search_messages: Substring search across messages.search_contacts: Find contacts by name or phone number.get_message_context: Get messages surrounding a specific message.get_my_profile: Get your own JID and profile info.update_contact: Update a contact's display name.sync_contacts: Import phone contacts from a VCF file.send_message: Send a text message (requires confirmation).send_file: Send a media file (requires confirmation).delete_message: Delete a message (requires confirmation).delete_chat: Delete an entire chat (requires confirmation).download_media: Download media from a message to disk.transcribe_voice_note: Transcribe a voice note to text.
License
MIT
This server cannot be deployed
Maintenance
Related MCP Connectors
WhatsApp CRM for AI agents: search contacts, read chats, manage the sales pipeline, send messages.
WhatsMCP connects Claude and other MCP-compatible AI agents directly to WhatsApp. Send and receive text, images, documents, and voice notes; manage groups (create, add/remove members, promote admins); look up contacts and profiles; follow channels; and read call and message history — all through a standard MCP interface. For voice use cases, WhatsMCP offers SIP-based calling plans (inbound-only, or full inbound/outbound) so AI voice agents can answer and place WhatsApp calls, plus low-latency WebSocket integrations with voice agent providers like ElevenLabs. Multiple WhatsApp accounts can be paired and managed per workspace, with webhook support for real-time inbound message delivery to your own infrastructure.
Drive WhatsApp from any MCP client: pair devices, send text and media, manage contacts and groups.
Give your AI agents a real WhatsApp number to send and receive messages.
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