About MCP Server for Intercom
MCP Server for Intercom lets AI assistants search Intercom conversations and tickets. It supports filtering by customer, status, dates, and message content, including email searches when no contact exists.
Key features
- 01Search conversations by date and content
- 02Find conversations by customer
- 03Filter tickets by status
- 04Find tickets by customer
- 05Search email content without a contact
Use cases
- 01Review conversations in a date range
- 02Find a customer's support history
- 03Track open, pending, or resolved tickets
MCP support
Exposes Intercom conversation and ticket search as MCP tools for compatible AI assistants.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP 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 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": "[email protected]",
"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": "[email protected]",
"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.
Comments
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