Intercom MCP Server

The Intercom MCP server transforms a company’s customer‑support archive into an AI‑ready data lake. By exposing the rich conversation and ticket history stored in Intercom through a standardized Model Context Protocol interface, it removes the friction that normally surrounds pulling data from a SaaS platform. Developers can now embed real‑time customer insights into Claude or other MCP‑compatible assistants without writing custom connectors, API wrappers, or handling authentication on the client side.

At its core, the server offers three focused tools: , , and . Each tool is designed to leverage Intercom’s own search API for server‑side filtering, which keeps payloads small and response times fast. Parameters such as date ranges, keywords, or customer identifiers are translated into efficient queries that return only the relevant threads or tickets. This means an assistant can answer questions like “Show me all billing‑related conversations from the past week” or “What tickets are still open for user X?” in a matter of seconds.

For developers building customer‑support workflows, this MCP server is a game‑changer. It enables use cases such as automated sentiment analysis of recent tickets, real‑time escalation alerts for high‑priority conversations, or dynamic FAQ generation based on the latest support interactions. Because the server is MCP‑compliant, any assistant that understands the protocol can invoke these tools directly, making it trivial to integrate into chat‑based help desks, knowledge bases, or internal analytics dashboards.

The server’s unique advantages lie in its tight coupling with Intercom’s native search capabilities and its lightweight, Docker‑ready deployment. A single environment variable supplies the API token, and the server exposes both a Glama‑specific and a standard runtime, allowing teams to choose between a fully integrated Glama experience or a leaner standalone service. This flexibility, combined with the declarative nature of MCP tools, gives developers a powerful yet straightforward way to bring live customer data into AI‑driven applications.