The MCP Server for Intercom enables AI assistants to access and analyze customer support data from Intercom with advanced search and filtering capabilities:
Search Intercom conversations by specific customers, keywords, date ranges, or email content (even when no contact exists)
Filter Intercom tickets by status (open, pending, resolved) or associated customer
Retrieve conversation history within specific date ranges (max 7 days)
Utilize efficient server-side filtering via Intercom's search API
Integrate seamlessly with MCP-compliant AI assistants for efficient customer support data analysis
Enables access and analysis of customer support data from Intercom, with capabilities for searching conversations and tickets using advanced filters, filtering by customer, status, date range, and keywords, and searching email content even without existing contacts.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Server for Intercomshow me open tickets from the last 3 days"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: Claude AI Documentation Assistant
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-mcpUsing 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:latestValidation 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:3000Alternative 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:latestThe 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 textexclude(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 dateendDate(DD/MM/YYYY) – Optional end datekeywords(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 dateendDate(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 dateendDate(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 testDisclaimer
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.