Twilio MCP Server

What does “Twilio” MCP Server do?

The Twilio MCP (Model Context Protocol) Server acts as a bridge between AI assistants and Twilio’s extensive suite of APIs. By exposing Twilio’s APIs as MCP tools, this server enables AI agents to interact programmatically with Twilio services, such as sending SMS messages, managing calls, or accessing account information. It streamlines development workflows by allowing AI-powered tools and assistants to perform operations like triggering communications, managing resources, and automating integrations without manual intervention. The server can be configured to expose specific Twilio APIs and is designed with security in mind, supporting robust authentication and providing options to filter which services are made available to clients. This makes it an essential tool for teams looking to embed communication capabilities directly into their AI workflows.

List of Prompts

No prompt templates were listed or described in the repository.

List of Resources

No explicit MCP resources were enumerated or described in the repository.

List of Tools

No explicit list of MCP tools was found in the repository root or documentation. However, it is mentioned that all of Twilio’s APIs are exposed as MCP Tools.

Use Cases of this MCP Server

• Twilio API Integration
  Allows developers to leverage Twilio’s messaging, voice, and communications APIs directly from AI-powered applications, enabling automated workflows such as sending SMS, making calls, or managing contacts.

• Automated Communication Workflows
  AI assistants can trigger Twilio-powered notifications, alerts, or reminders based on external events, improving automation for customer engagement or internal operations.

• Account and Resource Management
  Developers can build assistants that help manage Twilio account resources, including phone numbers, usage tracking, or billing, directly from within AI platforms.

• Filtered API Exposure
  The server can be configured to only expose selected Twilio services or endpoints, allowing for precise control over which functionalities are available to different AI agents or users.

How to set it up

Windsurf

1. Ensure you have Node.js installed.
2. Locate your Windsurf configuration file.
3. Add the Twilio MCP Server under mcpServers:

   {
     "mcpServers": {
       "twilio": {
         "command": "npx",
         "args": [
           "-y",
           "@twilio-alpha/mcp",
           "YOUR_ACCOUNT_SID/YOUR_API_KEY:YOUR_API_SECRET"
         ]
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify connectivity by checking if the MCP server appears in your Windsurf UI.

Securing API Keys

Use environment variables for sensitive data:

{
  "mcpServers": {
    "twilio": {
      "command": "npx",
      "args": [
        "-y",
        "@twilio-alpha/mcp"
      ],
      "env": {
        "TWILIO_API_CREDENTIALS": "YOUR_ACCOUNT_SID/YOUR_API_KEY:YOUR_API_SECRET"
      },
      "inputs": {
        "credentials": "${TWILIO_API_CREDENTIALS}"
      }
    }
  }
}

Claude

1. Install Node.js.
2. Open Claude’s configuration file.
3. Insert the Twilio MCP Server setup as shown in the Windsurf example above.
4. Save and reload Claude.
5. Check the MCP server’s availability in the Claude interface.

Cursor

1. Ensure Node.js is installed.
2. Open the Cursor configuration for MCP servers.
3. Add the Twilio MCP server configuration:

   {
     "mcpServers": {
       "twilio": {
         "command": "npx",
         "args": [
           "-y",
           "@twilio-alpha/mcp",
           "YOUR_ACCOUNT_SID/YOUR_API_KEY:YOUR_API_SECRET"
         ]
       }
     }
   }
   

4. Save the configuration and restart Cursor.
5. Verify the MCP server is listed.

Cline

1. Install Node.js if not present.
2. Locate the Cline MCP server configuration.
3. Add the Twilio MCP server block as in the previous examples.
4. Restart Cline after saving.
5. Confirm the server is active via the Cline dashboard.

Securing API Keys (applies to all platforms)

Use environment variables and reference them in your configuration as shown above.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "twilio": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “twilio” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

The Twilio MCP server is focused on exposing Twilio APIs as MCP tools, which is a valuable use case. However, the documentation in the repository is sparse regarding prompt templates, explicit resources, and a list of granular tools. Security best practices are addressed, and setup for various platforms is clear. While it covers the essentials, it lacks deeper documentation and transparency in some MCP-specific areas.

I would rate this MCP server a 5/10 for its clarity in setup and use, but with room for improvement in documentation of MCP-specific features.

MCP Score