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"
}

... View full README on GitHub