MCP Server for Intercom
This MCP server enables AI assistants to query and analyze Intercom customer support data via four search tools.
Search conversations by customer email or Intercom ID, with optional date range and keyword filters.
List conversations within a required date range (max 7 days), with optional keyword inclusion or exclusion filters.
Search tickets by status (open, pending, resolved), with optional date range.
Search tickets by customer email or Intercom ID, with optional date range.
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 "Deploy 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 Intercom show 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: jitbit-helpdesk-mcp
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.
Available Tools
4 toolslist_conversationsA
Retrieves Intercom conversations within a specific date range.
Required: startDate, endDate (DD/MM/YYYY format, max 7-day range) Optional: keyword, exclude (for content filtering)
Always ask for specific dates when user makes vague time references.
Inputs: endDate (required), startDate (required), exclude, keyword.
search_conversations_by_customerA
Searches for conversations by customer email or ID with optional date filtering.
Required: customerIdentifier (email/ID) Optional: startDate, endDate (DD/MM/YYYY format) Optional: keywords (array of terms to filter by)
Use when looking for conversation history with a specific customer.
Inputs: customerIdentifier (required), endDate, keywords, startDate.
search_tickets_by_customerB
Searches for tickets by customer email or ID with optional date filtering.
Required: customerIdentifier (email/ID) Optional: startDate, endDate (DD/MM/YYYY format)
Use when analyzing a customer's support history.
Inputs: customerIdentifier (required), endDate, startDate.
search_tickets_by_statusA
Searches for tickets by status with optional date filtering.
Required: status (one of: open, pending, resolved) Optional: startDate, endDate (DD/MM/YYYY format)
Use when analyzing support workload or tracking issue resolution.
Inputs: status (required), endDate, startDate.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 4 tools
The tools are mostly distinct with clear purposes: list_conversations retrieves all conversations in a date range, while the other three are specific searches (by customer for conversations/tickets, by status for tickets). However, search_conversations_by_customer and search_tickets_by_customer could be slightly confused since both target customers, but their descriptions clarify the resource difference (conversations vs. tickets).
All tool names follow a consistent verb_noun pattern with snake_case: list_conversations, search_conversations_by_customer, search_tickets_by_customer, search_tickets_by_status. The naming is predictable and readable throughout the set.
With only 4 tools, the set feels thin for an Intercom server, which typically handles a broader range of operations like creating/updating conversations, managing contacts, or sending messages. While the tools cover basic retrieval and search, the count is borderline low for the domain's potential scope.
The tool surface is significantly incomplete for an Intercom integration. It only provides search and list operations, missing essential CRUD actions like create_conversation, update_ticket, or delete operations. There are also gaps in managing other Intercom resources such as contacts, companies, or messages, which will limit agent capabilities.
Maintenance
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