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Connect AI tools to Intercom customer data and support tools — official
Learn how to use the Model Context Protocol (MCP) to enable AI agents to securely access and interact with your Intercom data whenever helpful.
Region availability Currently the Intercom MCP server is only supported in US hosted workspaces.
MCP is a protocol that enables AI tools and applications to connect with Intercom's data and services in a secure, standardized way. It provides a structured method for AI models to:
Intercom hosts a remote MCP server that follows the authenticated remote MCP specification (docs). This server handles requests from AI tools and provides access to Intercom data through a secure interface.
Connection URLs:
https://mcp.intercom.com/mcphttps://mcp.intercom.com/sse (deprecated, maintained for backwards compatibility)When an AI tool or application needs to access Intercom data:
The Intercom MCP Server provides 6 tools for interacting with the Intercom API:
Universal search tool for finding conversations and contacts using a query DSL approach.
Key Features:
object_type:conversations or object_type:contacts to indicate which API to callconversation_* or contact_*)starting_after parameterq: parameterExample Queries:
object_type:conversations state:open source_type:email
object_type:contacts email_domain:"example.com"
object_type:conversations source_body:contains:"refund" limit:20
Retrieve complete detailed information for specific resources.
Key Features:
conversation_ or contact_)Search conversations by specific IDs with advanced filtering options including source type, author details, state, and timing statistics.
Retrieve a single conversation by ID with complete details including all conversation parts and metadata.
Search contacts by IDs, name, email, phone, custom attributes, or email domain with flexible matching options.
Get complete contact information including custom attributes, location data, and activity timestamps.
The MCP server supports two authentication approaches:
Configuration Guide The examples below are generic templates. Always refer to your specific LLM provider's official documentation for the most up-to-date configuration instructions, as setup details may vary between versions and providers.
For OAuth authentication (recommended):
{
"mcpServers": {
"intercom": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.intercom.com/mcp"
]
}
}
}
For Bearer token authentication:
{
"mcpServers": {
"intercom": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.intercom.com/mcp",
"--header",
"Authorization:${AUTH_HEADER}"
],
"env": {
"AUTH_HEADER": "Bearer YOUR_INTERCOM_API_TOKEN"
}
}
}
}
Each AI provider has specific setup instructions for MCP servers. Please consult the official documentation for your provider:
https://mcp.intercom.com/mcpThe Intercom MCP server requires the following permissions to access your workspace data. When using Bearer token authentication, ensure your access token includes these scopes. Learn more about OAuth permissions.
Test the connection using:
npx @modelcontextprotocol/inspector
Then connect to:
https://mcp.intercom.com/mcp (or /sse for legacy)# Kill existing connections
pkill -f mcp-remote
# Clear MCP auth cache
rm -rf ~/.mcp-auth
# Test direct connection
npx mcp-remote https://mcp.intercom.com/mcp
# With bearer token
npx mcp-remote https://mcp.intercom.com/mcp --header "Authorization:Bearer YOUR_TOKEN"
ps aux | grep mcp-remote | grep -v grep
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