About Voicebot-MCP-Server
Voicebot-MCP-Server connects Claude Desktop with WhatsApp through an MCP server, enabling voice messages to be sent and received. It is intended for interactions between an AI client and a messaging app.
Key features
- 01Send voice messages
- 02Receive voice messages
- 03Interact through WhatsApp
- 04Connect with Claude Desktop
Use cases
- 01Send voice messages from Claude Desktop
- 02Receive WhatsApp voice messages
- 03Interact with Claude Desktop through messaging
MCP support
The server provides an MCP interface for Claude Desktop and uses WhatsApp to send and receive voice messages.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEVoicebot-MCP-Server
This is a MCP Server which provides capabilities to send and receive voice messages and interact with AI client Claude Desktop via messaging app WhatsApp.
Required Libraries:
The different libraries and dependencies required for the project are as given below:
- MCP SDK
- dotenv (for storing .env files)
- requests
- json
- uv (for testing with MCP Inspector)
- Flask
- Twilio
Steps to run:
- Install required libraries
pip install flask twilio uv dotenv
- Install the MCP SDK.
pip install "mcp[cli]"
- Integrate the server with Claude Desktop
mcp install server.py --name "VoiceBot MCP Server"
- Test the server using MCP Inspector
mcp dev server.py
- Run the Webhook using ngrok
ngrok http 5003
Note: In whatsapp_webhook.py, personal whatsapp numbers can be provided in "WHATSAPP_VERIFY_NUMBER" for interacting with the Claude-based MCP Server.
The required API tokens and IDs were maintained in a .env file.
Certified by MCPHub. Find it here.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.