OTRS MCP Server

Overview

The OTRS MCP Server bridges the gap between AI assistants and the Open Ticket Request System (OTRS) by exposing OTRS’s rich ticketing and configuration item capabilities through the Model Context Protocol (MCP). This integration allows an AI assistant to act as a first‑line support agent, automatically creating, updating, and querying tickets while respecting the same authentication and permission model that OTRS users rely on. For developers building intelligent support workflows, the server removes the need to write custom API wrappers and instead leverages MCP’s standardized interface for seamless tool discovery and invocation.

At its core, the server translates MCP commands into calls against OTRS’s Generic Interface. It supports full CRUD operations on tickets, retrieval of ticket history, and search functionality that can be fine‑tuned with default values such as queue, state, priority, and type. In addition to ticket management, the server provides access to configuration items (CMDB objects), enabling an AI assistant to pull or update asset data, service definitions, and other configuration records. Session management is handled transparently; the server creates a session with OTRS, caches it, and renews it as needed, ensuring that all operations remain authenticated without exposing credentials to the assistant.

Key capabilities include:

• Ticket lifecycle management: Create, read, update, and search tickets with optional default parameters for queue, state, priority, and type.
• History access: Retrieve detailed ticket history to provide context during conversations or audits.
• CMDB interaction: Manage configuration items, allowing AI agents to reference or modify asset information.
• Security and reliability: Session handling, SSL/TLS support with optional certificate verification, and configurable default values protect data integrity while simplifying usage.
• Tool configurability: Developers can enable or disable individual tools, tailoring the assistant’s capabilities to specific business rules or compliance requirements.
• Containerization: A pre‑built Docker image streamlines deployment, while the server can also run directly via UV for environments that prefer lightweight execution.

Typical use cases span from automated incident triage—where an AI assistant opens a ticket based on user input—to proactive monitoring, where it updates tickets or configuration items in response to system alerts. In customer support centers, the server enables chatbots to provide instant ticket creation and status checks without routing users through a web portal. In IT operations, the same assistant can pull configuration data to diagnose issues or modify CMDB entries when a change request is approved. By exposing OTRS functionality through MCP, developers gain a unified, AI‑centric interface that aligns with modern conversational workflows and reduces the overhead of maintaining separate API clients.