jira-digest-mcp

A small MCP server that exposes one tool, get_resolved_issues, for querying resolved Jira tickets across multiple Atlassian Cloud sites using a single (email, API token) credential pair. Designed for executive summarization of dev activity across a portfolio of companies.

Install

uv tool install jira-digest-mcp

Or, from a checkout:

uv sync
uv run jira-digest-mcp

Required environment variables

• JIRA_USERNAME — the email address tied to your Atlassian API token.
• JIRA_API_TOKEN — an API token from https://id.atlassian.com/manage-profile/security/api-tokens.

Optional:

• LOG_LEVEL — INFO (default) or DEBUG. Logs go to stderr.

MCP tool

get_resolved_issues

get_resolved_issues(
    base_url: str,        # e.g. "https://example.atlassian.net"
    project_key: str,     # e.g. "ST"
    since: str,           # "2026-04-01" or "-7d", "-2w"
    until: str | None,    # optional, same forms
    max_results: int = 100,
) -> list[dict]

Each returned dict contains: key, summary, issue_type, status, resolution, resolved_date, assignee_display_name, priority, labels, components, parent_key, parent_summary, story_points.

story_points is auto-discovered per site by matching the field name "Story Points" (case-insensitive). If the field has been renamed on a given site, story points will be null for that site.

Claude Desktop / Claude Code config

Add to your MCP client config:

{
  "mcpServers": {
    "jira-digest": {
      "command": "uv",
      "args": ["tool", "run", "jira-digest-mcp"],
      "env": {
        "JIRA_USERNAME": "you@example.com",
        "JIRA_API_TOKEN": "..."
      }
    }
  }
}

If you installed from a checkout, see the Development section below for the equivalent MCP client config that points at your local source.

Development

The source lives at D:\src\AI\jira-digest-mcp.

Setup

From the repo root:

uv sync

Tests

uv run pytest -v

Running the server from source

To start the stdio server directly (it will hang waiting for JSON-RPC on stdin, which is correct — interrupt with Ctrl-C when done):

$env:JIRA_USERNAME = "you@example.com"
$env:JIRA_API_TOKEN = "..."
uv run --project D:\src\AI\jira-digest-mcp jira-digest-mcp

Set $env:LOG_LEVEL = "DEBUG" to see request-level logs on stderr.

Pointing Claude Desktop / Claude Code at the dev checkout

Use this MCP client config block to run the server from source instead of an installed copy:

{
  "mcpServers": {
    "jira-digest-dev": {
      "command": "uv",
      "args": [
        "run",
        "--project",
        "D:\\src\\AI\\jira-digest-mcp",
        "jira-digest-mcp"
      ],
      "env": {
        "JIRA_USERNAME": "you@example.com",
        "JIRA_API_TOKEN": "...",
        "LOG_LEVEL": "DEBUG"
      }
    }
  }
}

After editing a source file, restart the MCP client (or use its "reload MCP servers" action) to pick up the change.

Releases

Releases publish to PyPI automatically when a v* tag is pushed. The workflow lives at .github/workflows/publish.yml and uses PyPI Trusted Publishing (OIDC) — no API token is stored in the repo.

One-time setup (already done for this repo)

1. On PyPI, go to the project's Publishing settings and add a pending or active trusted publisher with:
   • Owner: the GitHub org/user
   • Repository: jira-digest-mcp
   • Workflow filename: publish.yml
   • Environment name: pypi
2. In GitHub, create an environment named pypi under Settings → Environments. Optionally add a required-reviewer protection rule so a human has to approve each publish.

Cutting a release

1. Bump version in pyproject.toml following semantic versioning:
   • MAJOR — breaking changes to the MCP tool surface (removing/renaming tools or arguments, changing types, removing response fields).
   • MINOR — backward-compatible additions (new tool, new optional argument, new response field).
   • PATCH — bug fixes, refactors, docs, dependency bumps that don't alter behavior.
2. Commit the bump (and any release notes) and push to main.
3. Tag the commit and push the tag:

   git tag v0.2.0     # must match the pyproject.toml version exactly
   git push origin v0.2.0
   

4. The Publish to PyPI workflow runs on the tag push, builds with uv build, and uploads with uv publish. Watch it under the repo's Actions tab.

The tag and pyproject.toml version must agree — uv build reads the version from pyproject.toml, so a mismatched tag will silently publish under the wrong version number.