Model Context Protocol (MCP)

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.

What is Model Context Protocol?

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:

• Find and retrieve Intercom data (conversations, contacts, etc.)
• Access specific tools and functionality provided by Intercom
• Maintain context about your Intercom workspace when working with AI assistants

How MCP Works

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:

• Streamable HTTP (Recommended): https://mcp.intercom.com/mcp
• Legacy SSE: https://mcp.intercom.com/sse (deprecated, maintained for backwards compatibility)

When an AI tool or application needs to access Intercom data:

1. The tool connects to Intercom’s MCP server
2. Authentication verifies the user’s permissions
3. The tool can then access relevant Intercom data and functionality
4. The connection remains live to receive updates as needed

Benefits of Using MCP

• Secure Access: All data access is authenticated and authorized
• Standardized Interface: Consistent interaction pattern across different AI tools
• Contextual Understanding: AI assistants maintain awareness of your Intercom environment
• Increased Development Efficiency: Retrieve and interpret customer data from Intercom via your internal AI tools to be more efficient in your work

Available Tools

The Intercom MCP Server provides 6 tools for interacting with the Intercom API:

Universal Tools

search

Universal search tool for finding conversations and contacts using a query DSL approach.

Key Features:

• Must specify object_type:conversations or object_type:contacts to indicate which API to call
• Supports complex field-based queries with operators (eq, neq, gt, lt, contains, etc.)
• Returns summary results with IDs prefixed by type (conversation_* or contact_*)
• Built-in pagination support with starting_after parameter
• Free-text search capability with q: parameter

Example 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

fetch

Retrieve complete detailed information for specific resources.

Key Features: