mcp-server-for-intercom

mcp-server-for-intercom avatar

by raoulbia-ai

What is mcp-server-for-intercom

MCP Server for Intercom

An MCP-compliant server that enables AI assistants to access and analyze customer support data from Intercom.

Features

  • Search conversations and tickets with advanced filtering
  • Filter by customer, status, date range, and keywords
  • Search by email content even when no contact exists
  • Efficient server-side filtering via Intercom's search API
  • Seamless integration with MCP-compliant AI assistants

Installation

Prerequisites

  • Node.js 18.0.0 or higher
  • An Intercom account with API access
  • Your Intercom API token (available in your Intercom account settings)

Quick Setup

Using NPM

# Install the package globally
npm install -g mcp-server-for-intercom

# Set your Intercom API token
export INTERCOM_ACCESS_TOKEN="your_token_here"

# Run the server
intercom-mcp

Using Docker

The default Docker configuration is optimized for Glama compatibility:

# Start Docker (if not already running)
# On Windows: Start Docker Desktop application
# On Linux: sudo systemctl start docker

# Build the image
docker build -t mcp-intercom .

# Run the container with your API token and port mappings
docker run --rm -it -p 3000:3000 -p 8080:8080 -e INTERCOM_ACCESS_TOKEN="your_token_here" mcp-intercom:latest

Validation Steps:

# Test the server status
curl -v http://localhost:8080/.well-known/glama.json
# Test the MCP endpoint
curl -X POST -H "Content-Type: application/json" -d '{"jsonrpc":"2.0","id":1,"method":"mcp.capabilities"}' http://localhost:3000
Alternative Standard Version

If you prefer a lighter version without Glama-specific dependencies:

# Build the standard image
docker build -t mcp-intercom-standard -f Dockerfile.standard .

# Run the standard container
docker run --rm -it -p 3000:3000 -p 8080:8080 -e INTERCOM_ACCESS_TOKEN="your_token_here" mcp-intercom-standard:latest

The default version includes specific dependencies and configurations required for integration with the Glama platform, while the standard version is more lightweight.

Available MCP Tools

1. list_conversations

Retrieves all conversations within a date range with content filtering.

Parameters:

  • startDate (DD/MM/YYYY) – Start date (required)
  • endDate (DD/MM/YYYY) – End date (required)
  • keyword (string) – Filter to include conversations with this text
  • exclude (string) – Filter to exclude conversations with this text

Notes:

  • Date range must not exceed 7 days
  • Uses efficient server-side filtering via Intercom's search API

Example:

{
  "startDate": "15/01/2025",
  "endDate": "21/01/2025",
  "keyword": "billing"
}

2. search_conversations_by_customer

Finds conversations for a specific customer.

Parameters:

  • customerIdentifier (string) – Customer email or Intercom ID (required)
  • startDate (DD/MM/YYYY) – Optional start date
  • endDate (DD/MM/YYYY) – Optional end date
  • keywords (array) – Optional keywords to filter by content

Notes:

  • Can find conversations by email content even if no contact exists
  • Resolves emails to contact IDs for efficient searching

Example:

{
  "customerIdentifier": "customer@example.com",
  "startDate": "15/01/2025",
  "endDate": "21/01/2025",
  "keywords": ["billing", "refund"]
}

3. search_tickets_by_status

Retrieves tickets by their status.

Parameters:

  • status (string) – "open", "pending", or "resolved" (required)
  • startDate (DD/MM/YYYY) – Optional start date
  • endDate (DD/MM/YYYY) – Optional end date

Example:

{
  "status": "open",
  "startDate": "15/01/2025",
  "endDate": "21/01/2025"
}

4. search_tickets_by_customer

Finds tickets associated with a specific customer.

Parameters:

  • customerIdentifier (string) – Customer email or Intercom ID (required)
  • startDate (DD/MM/YYYY) – Optional start date
  • endDate (DD/MM/YYYY) – Optional end date

Example:

{
  "customerIdentifier": "customer@example.com",
  "startDate": "15/01/2025",
  "endDate": "21/01/2025"
}

Configuration with Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "intercom-mcp": {
      "command": "intercom-mcp",
      "args": [],
      "env": {
        "INTERCOM_ACCESS_TOKEN": "your_intercom_api_token"
      }
    }
  }
}

Implementation Notes

For detailed technical information about how this server integrates with Intercom's API, see src/services/INTERCOM_API_NOTES.md. This document explains our parameter mapping, Intercom endpoint usage, and implementation details for developers.

Development

# Clone and install dependencies
git clone https://github.com/raoulbia-ai/mcp-server-for-intercom.git
cd mcp-server-for-intercom
npm install

# Build and run for development
npm run build
npm run dev

# Run tests
npm test

Disclaimer

This project is an independent integration and is not affiliated with, officially connected to, or endorsed by Intercom Inc. "Intercom" is a registered trademark of Intercom Inc.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.