Jira CLI MCP Server

The Jira CLI MCP Server bridges the gap between conversational AI assistants and Atlassian’s ticketing system by wrapping the well‑known command‑line tool in an MCP interface. Developers can therefore issue natural‑language requests to Claude or other AI agents and have those commands executed against a real Jira instance without exposing raw API tokens or writing custom integration code. This server turns any existing installation into a first‑class AI‑ready service, preserving the authentication flow and environment that teams already rely on.

At its core, the server exposes a small but powerful set of actions: creating tickets, querying with JQL, retrieving full issue details (including comments), updating descriptions, adding Markdown‑styled comments, assigning work to the current user, moving issues between statuses, and opening tickets directly in a web browser. Each action is implemented as an MCP tool that the AI can invoke by name, passing structured arguments. Because it operates through the CLI rather than the REST API, the server inherits all of ’s flexibility—support for custom fields, workflows, and project configurations—while keeping the runtime lightweight (a single Bun process) and avoiding Docker containers or bundled API clients.

For teams that already use for day‑to‑day operations, this MCP server offers a seamless upgrade path: no new credentials are required, and the same local configuration files (typically ) remain in use. Security is therefore enhanced—API tokens never leave the local machine, and the server relies on the CLI’s own OAuth or cookie‑based authentication. Developers can immediately add the MCP to Claude Desktop by pointing it at the binary, enabling a new dimension of productivity: an AI that can draft tickets from meeting notes, pull the latest status updates during a stand‑up, or automatically reassign blockers without leaving the chat.

Typical use cases include automated sprint planning where the AI generates backlog items from a product vision document, continuous integration pipelines that notify stakeholders of build failures by creating Jira tickets, or customer support workflows where the AI triages incoming emails and populates issues. In each scenario, the MCP server removes friction—no manual API calls or authentication prompts—and lets developers focus on higher‑level logic.

What sets this server apart is its minimal footprint and deep integration with an existing toolchain. It eliminates the need for self‑hosted API gateways or complex SDKs, while still providing full access to Jira’s feature set. The result is a lean, secure, and developer‑friendly bridge that empowers AI assistants to act as true collaborators in the software development lifecycle.