by lharries
Send and receive WhatsApp messages directly from Claude and other AI assistants. Search conversations, manage contacts,
★ 5.4K
GitHub stars
Send and receive WhatsApp messages directly through Claude, with access to your personal message history stored locally in SQLite.
WhatsApp MCP is a community-built MCP server published by lharries that provides AI assistants with tools and capabilities via the Model Context Protocol. Send and receive WhatsApp messages directly from Claude and other AI assistants. Search conversations, manage contacts, It is categorized under communication, developer tools.
You can install WhatsApp MCP in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
WhatsApp MCP is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Strong directory entry: WhatsApp MCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Strong directory entry: WhatsApp MCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
WhatsApp MCP has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, WhatsApp MCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
According to our notes, WhatsApp MCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
WhatsApp MCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
WhatsApp MCP is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: WhatsApp MCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
WhatsApp MCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated WhatsApp MCP against two servers with overlapping tools; this profile had the clearer scope statement.
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This is a Model Context Protocol (MCP) server for WhatsApp.
With this you can search and read your personal Whatsapp messages (including images, videos, documents, and audio messages), search your contacts and send messages to either individuals or groups. You can also send media files including images, videos, documents, and audio messages.
It connects to your personal WhatsApp account directly via the Whatsapp web multidevice API (using the whatsmeow library). All your messages are stored locally in a SQLite database and only sent to an LLM (such as Claude) when the agent accesses them through tools (which you control).
Here's an example of what you can do when it's connected to Claude.

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Caution: as with many MCP servers, the WhatsApp MCP is subject to the lethal trifecta. This means that project injection could lead to private data exfiltration.
curl -LsSf https://astral.sh/uv/install.sh | sh.ogg Opus format. With FFmpeg installed, the MCP server will automatically convert non-Opus audio files. Without FFmpeg, you can still send raw audio files using the send_file tool.Clone this repository
git clone https://github.com/lharries/whatsapp-mcp.git
cd whatsapp-mcp
Run the WhatsApp bridge
Navigate to the whatsapp-bridge directory and run the Go application:
cd whatsapp-bridge
go run main.go
The first time you run it, you will be prompted to scan a QR code. Scan the QR code with your WhatsApp mobile app to authenticate.
After approximately 20 days, you will might need to re-authenticate.
Connect to the MCP server
Copy the below json with the appropriate {{PATH}} values:
{
"mcpServers": {
"whatsapp": {
"command": "{{PATH_TO_UV}}", // Run `which uv` and place the output here
"args": [
"--directory",
"{{PATH_TO_SRC}}/whatsapp-mcp/whatsapp-mcp-server", // cd into the repo, run `pwd` and enter the output here + "/whatsapp-mcp-server"
"run",
"main.py"
]
}
}
}
For Claude, save this as claude_desktop_config.json in your Claude Desktop configuration directory at:
~/Library/Application Support/Claude/claude_desktop_config.json
For Cursor, save this as mcp.json in your Cursor configuration directory at:
~/.cursor/mcp.json
Restart Claude Desktop / Cursor
Open Claude Desktop and you should now see WhatsApp as an available integration.
Or restart Cursor.
If you're running this project on Windows, be aware that go-sqlite3 requires CGO to be enabled in order to compile and work properly. By default, CGO is disabled on Windows, so you need to explicitly enable it and have a C compiler installed.
Install a C compiler
We recommend using MSYS2 to install a C compiler for Windows. After installing MSYS2, make sure to add the ucrt64\bin folder to your PATH.
→ A step-by-step guide is available here.
Enable CGO and run the app
cd whatsapp-bridge
go env -w CGO_ENABLED=1
go run main.go
Without this setup, you'll likely run into errors like:
Binary was compiled with 'CGO_ENABLED=0', go-sqlite3 requires cgo to work.
This application consists of two main components:
Go WhatsApp Bridge (whatsapp-bridge/): A Go application that connects to WhatsApp's web API, handles authentication via QR code, and stores message history in SQLite. It serves as the bridge between WhatsApp and the MCP server.
Python MCP Server (whatsapp-mcp-server/): A Python server implementing the Model Context Protocol (MCP), which provides standardized tools for Claude to interact with WhatsApp data and send/receive messages.
whatsapp-bridge/store/ directoryOnce connected, you can interact with your WhatsApp contacts through Claude, leveraging Claude's AI capabilities in your WhatsApp conversations.
Claude can access the following tools to interact with WhatsApp:
The MCP server supports both sending and receiving various media types:
You can send various media types to your WhatsApp contacts:
send_file tool to share any supported media type.send_audio_message tool to send audio files as playable WhatsApp voice messages.
.ogg Opus format.send_file tool, but they won't appear as playable voice messages.By default, just the metadata of the media is stored in the local database. The message will indicate that media was sent. To access this media you need to use the download_media tool which takes the message_id and chat_jid (which are shown when printing messages containing the meda), this downloads the media and then returns the file path which can be then opened or passed to another tool.
whatsapp-bridge/store/messages.db and whatsapp-bridge/store/whatsapp.db) and restart the bridge to re-authenticate.For additional Claude Desktop integration troubleshooting, see the MCP documentation. The documentation includes helpful tips for checking logs and resolving common issues.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.