MCP server exposing a get_resolved_issues tool that queries resolved Jira tickets across multiple Atlassian Cloud sites with one credential pair.
Project description
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) orDEBUG. 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)
- 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
- In GitHub, create an environment named
pypiunder Settings → Environments. Optionally add a required-reviewer protection rule so a human has to approve each publish.
Cutting a release
- Bump
versioninpyproject.tomlfollowing 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.
- Commit the bump (and any release notes) and push to
main. - 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
- The
Publish to PyPIworkflow runs on the tag push, builds withuv build, and uploads withuv 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.
Project details
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