Request Tracker MCP Server

The Request Tracker MCP Server bridges the gap between conversational AI assistants and the legacy ticketing platform Request Tracker. By exposing a lightweight, standard‑compliant MCP endpoint, it allows AI agents such as Claude to query and manipulate ticket data without the need for custom adapters or manual API wrappers. This solves a common pain point for organizations that still rely on Request Tracker: the lack of modern, AI‑friendly interfaces to their issue queues.

At its core, the server implements two essential operations that reflect everyday support workflows. First, it can retrieve a ticket’s status when supplied with an identifier—mirroring the typical “What is the current state of ticket #1234?” question. Second, it can create new tickets by parsing natural‑language intent into a queue and subject line, such as “Create a ticket on the General queue to reset my password.” These actions are performed through secure calls to Request Tracker’s REST API, with authentication handled via environment configuration.

For developers, this means a plug‑and‑play component that can be dropped into any MCP‑compatible AI stack. The server’s configuration is minimal: a single file holds the Request Tracker URL, API credentials, and optional queue mappings. Once running, any AI client that understands MCP can request ticket status or initiate new tickets by sending a simple JSON payload. The server translates these requests into the appropriate REST calls, then returns a concise response that the AI can relay back to the user.

Real‑world scenarios abound: a help desk chatbot could automatically open tickets for password resets, while an internal operations bot might surface the progress of a critical incident ticket. Because the server operates over HTTP, it can be deployed behind existing corporate proxies or integrated into container orchestration platforms. Its lightweight nature also makes it ideal for edge deployments where latency and resource usage are critical.

Unique advantages include zero‑code integration with existing MCP clients—developers need not write new prompts or handlers. The server also centralizes authentication and queue mapping, reducing duplication across multiple assistants. Finally, by abstracting Request Tracker’s idiosyncratic API behind a clean MCP interface, it future‑proofs workflows against platform upgrades or migrations.