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A2atlassian

  • Updated April 23, 2026
  • agentic-eng/a2atlassian

a2atlassian is a MCP server that gives AI agents compact, pre-wired access to Jira and Confluence.

About

a2atlassian is a stdio MCP server from agentic-eng that connects AI coding agents to Jira and Confluence with pre-configured connections and deliberately compact responses, aimed at developers and tiny teams who live in Atlassian for tickets and docs but hate pasting issue keys and wiki clutter into every prompt. Register a2atlassian in Claude Code or Cursor during build and pm work so the agent can fetch issues, pages, and project context while you implement, write launch notes, or reconcile specs with code. Compact output is the differentiator: it trades maximal API fidelity for agent-usable summaries, which fits iterative shipping more than enterprise ETL. You still need valid Atlassian credentials and site URLs; this is not a replacement for Jira automation rules or Confluence publishing pipelines. Skip if you do not use Atlassian or need full administrative CRUD across every REST edge case.

  • Jira and Confluence tools tailored for AI agents
  • Pre-configured connections to reduce setup friction
  • Compact output format to save context window versus raw REST dumps
  • stdio PyPI package a2atlassian v0.2.0

A2atlassian by the numbers

  • Data as of Jul 7, 2026 (Skillselion catalog sync)
terminal
claude mcp add a2atlassian -- uvx a2atlassian

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Packagea2atlassian
TransportSTDIO
AuthNone
Last updatedApril 23, 2026
Repositoryagentic-eng/a2atlassian

What it does

Give your coding agent compact Jira and Confluence access for tickets, specs, and status without bulky default API dumps.

Who is it for?

shippers on Atlassian Cloud who want agent-side backlog and wiki context during feature work.

Skip if: Skip if you're on Linear-only stacks, air-gapped wikis, or admins and need exhaustive mutating Jira automation via MCP.

What you get

Your agent reads and reasons over Jira and Confluence data in compact form so tickets and specs stay synced with implementation chat.

  • Agent-readable Jira issue and project context
  • Confluence page content in compact form for implementation
  • Less context-window waste versus raw Atlassian API JSON

By the numbers

  • Covers Jira and Confluence (two Atlassian products)
  • PyPI identifier a2atlassian version 0.2.0
  • Registry name io.github.agentic-eng/a2atlassian with stdio transport
README.md

🏢 a2atlassian

Agent-to-Atlassian

Give AI agents access to Jira and Confluence. Save credentials once, work from anywhere.

Jira + Confluence · read-only by default · pre-configured connections · compact TSV output

PyPI Python License CI MCP Registry

Quick Start · MCP Tools · Security · Comparison · Setup


Agent: "What's the status of PROJ-42? Add a comment with the progress update."
  ↓
a2atlassian → get issue, add comment, transition to In Progress
  ↓
Agent: "Done — PROJ-42 updated and moved to In Progress."

Why a2atlassian?

Existing Atlassian MCP servers (Rovo, sooperset) require Docker, .env files, and mcp-remote bridges. They dump 72 tools into agent context and have known quirks that silently fail. a2atlassian fixes all of that:

  • No Dockerpip install a2atlassian and you're done
  • Pre-configured connections — define projects in .mcp.json with --register, agent works immediately
  • Read-only by default — write access is opt-in per connection
  • Connection scoping--scope limits which projects an agent can see
  • Compact output — TSV for lists (30-60% fewer tokens), JSON for single entities
  • Dynamic tool loading — MCP clients that support deferred tools (e.g., Claude Code) load tools on demand, keeping context lean
  • Error enrichment — bad field names get suggestions, JQL typos get corrections, quirks get auto-fixed
  • Secrets stay in env${ATLASSIAN_TOKEN} in configs, expanded only at runtime

Scope today: full Jira surface (issues, comments, sprints, boards, worklogs, links, versions, fields, watchers, projects) and Confluence core (pages CRUD, search, metadata-only writes).

Quick Start

# Recommended — installs globally as a CLI tool
uv tool install a2atlassian

# Or with pip
pip install a2atlassian

As an MCP Server (recommended)

Claude Code (with pre-configured connection):

claude mcp add -s user a2atlassian -- uvx --from a2atlassian a2atlassian-mcp \
  --register myproject https://mysite.atlassian.net user@company.com '${ATLASSIAN_TOKEN}'

Claude Code (minimal — agent calls login on demand):

claude mcp add -s user a2atlassian -- uvx --from a2atlassian a2atlassian-mcp

Claude Desktop / Cursor / any MCP client (.mcp.json):

{
  "mcpServers": {
    "a2atlassian": {
      "command": "uvx",
      "args": [
        "--from", "a2atlassian", "a2atlassian-mcp",
        "--register", "myproject", "https://mysite.atlassian.net",
        "user@company.com", "${ATLASSIAN_TOKEN}"
      ],
      "env": {
        "ATLASSIAN_TOKEN": "your-api-token-here"
      }
    }
  }
}

Multiple projects:

{
  "args": [
    "--from", "a2atlassian", "a2atlassian-mcp",
    "--register", "myproject", "https://mysite.atlassian.net", "user@a.com", "${TOKEN_A}",
    "--register", "personal", "https://personal.atlassian.net", "user@b.com", "${TOKEN_B}"
  ]
}

Scoped connections (limit agent to specific saved projects):

{
  "args": ["--from", "a2atlassian", "a2atlassian-mcp", "--scope", "myproject"]
}

--register creates ephemeral in-memory connections (process lifetime, no files written). --scope filters which saved connections are visible. Both limit blast radius.

As a CLI

# Save a connection (validates by calling /myself)
a2atlassian login -c myproject \
  --url https://mysite.atlassian.net \
  --email user@company.com \
  --token "$ATLASSIAN_TOKEN"

# Same, pulling the token from 1Password via `op`
a2atlassian login -c myproject \
  --url https://mysite.atlassian.net \
  --email user@company.com \
  --token "op://Personal/Atlassian/token"

# Enable writes
a2atlassian login -c myproject \
  --url https://mysite.atlassian.net \
  --email user@company.com \
  --token "$ATLASSIAN_TOKEN" \
  --no-read-only

# List / remove connections
a2atlassian connections
a2atlassian logout -c myproject

Tokens accept three forms: literal value, ${ENV_VAR} reference, or op://vault/item/field (resolved via the 1Password CLI at runtime).

MCP Tools

Connection Management

Tool Description
login Save a connection — validates by calling /myself first
logout Remove a saved connection
list_connections List connections (no secrets exposed)

Jira — Read

Tool Description
jira_get_issue Get issue by key — full fields, status, assignee
jira_search Search by JQL with pagination — compact TSV output by default
jira_search_count Count-only JQL — cheap pre-check for "is this going to be huge?"
jira_search_fields Discover custom-field IDs by name
jira_get_field_options List allowed values for a select / multi-select field
jira_get_comments Get all comments for an issue
jira_get_worklogs Get all worklogs for an issue
jira_get_transitions Discover available status transitions
jira_get_link_types List available issue-link types
jira_get_watchers List watchers for an issue
jira_get_projects List projects accessible to the connection
jira_get_project_metadata Fetch creation metadata (issue types, required fields)
jira_get_user_profile Resolve an email/accountId to a full user profile
jira_get_boards List agile boards in a project
jira_get_board_issues Issues on a board (paginated)
jira_get_sprints List sprints on a board
jira_get_sprint_issues Issues in a sprint (paginated)

Jira — Write (requires read-write connection)

Tool Description
jira_create_issue Create a new issue
jira_update_issue Update fields on an existing issue
jira_delete_issue Delete an issue
jira_transition_issue Move issue to a new status
jira_add_comment Add comment (wiki markup, API v2)
jira_edit_comment Update existing comment
jira_add_worklog Log time on an issue
jira_create_issue_link Link two issues
jira_remove_issue_link Remove an issue link
jira_set_watchers Replace the watcher set on an issue
jira_create_sprint Create a sprint on a board
jira_update_sprint Update sprint state / dates
jira_add_issues_to_sprint Move issues into a sprint
jira_create_version Create a project version

Confluence — Read

Tool Description
confluence_get_page Fetch a page by id (body storage, version, space)
confluence_get_page_children List direct children of a page (paginated)
confluence_search CQL search; minimal per-match rows

Confluence — Write (requires read-write connection)

Tool Description
confluence_upsert_pages Batch create-or-update with preserve-on-omit body semantics + per-page status + partial-failure shape
confluence_set_page_properties Metadata-only write (page_width, emoji, labels) — physically cannot touch body or title

Output Formats

All tools accept a format parameter:

Format Default for Description
toon Lists (search, comments) TSV with header — shape once, data many. 30-60% fewer tokens than JSON
json Single entities (get_issue) Standard JSON with metadata envelope

List responses use a compact TSV-style format (header row + tab-separated values) inspired by TOON. This is the same approach a2db uses — column names appear once, then just values. For a 50-issue search result, this typically saves 40-60% of tokens compared to JSON.

TSV example (search results):

# search (23 results, 50ms, truncated: False)
key	summary	assignee	status
PROJ-142	Fix auth timeout	Alice Smith	In Progress
PROJ-141	Add search filters	Bob Jones	To Do

JSON example (single issue):

{
  "data": {"key": "PROJ-142", "fields": {"summary": "Fix auth timeout", ...}},
  "count": 1,
  "truncated": false,
  "time_ms": 85
}

Error Enrichment

When something fails, a2atlassian tells the agent what to do:

Field 'asignee' does not exist
Did you mean: assignee?
Connection 'myproject' is read-only.
Run: a2atlassian login -p myproject --read-only false

Quirks handled automatically:

  • Assignee requires display name (not 712020: account IDs) — auto-detected with hint
  • Parent field must be plain string — {"key": "PROJ-14"} normalized to "PROJ-14" silently
  • Issue type conversion not supported via API — clear Jira UI instructions provided

Security

Read-Only by Default

Every connection starts read-only. Write tools check the connection flag before executing:

Connection 'myproject' is read-only.
Re-run 'a2atlassian login -p myproject --read-only false' to enable writes.

The human operator controls write access — not the agent.

Credential Storage

Connections saved via login go to ~/.config/a2atlassian/connections/ as TOML files:

  • File permissions: 0600 (owner read/write only)
  • ${ATLASSIAN_TOKEN} syntax — env var references stored literally, expanded at runtime
  • No secrets in outputlist_connections shows project name, URL, and mode — never tokens
  • Ephemeral mode--register keeps credentials in memory only, never written to disk

Connection Scoping

Use --scope to limit which saved connections a specific MCP instance can access:

# Project config — only myproject visible, even if other connections are saved
uvx --from a2atlassian a2atlassian-mcp --scope myproject

Project-level MCP configs (.claude/mcp.json) override global configs — each repo sees only its own connections.

Rate Limiting

Built-in retry with exponential backoff for Atlassian's rate limits (429) and transient server errors (500). Two retries at 1s and 3s intervals before surfacing the error.

Comparison

Feature a2atlassian Rovo (official) sooperset/mcp-atlassian
Setup pip install OAuth + Docker Docker + .env + mcp-remote
Tools in context ~35 (loaded on demand) ~72 ~72
Connection management TOML + --register + --scope Per-session OAuth .env file
Multi-project Yes (scoped) No One .env per setup
Read-only default Yes (per-connection) No No
Output format TSV + JSON JSON JSON
Error enrichment Field suggestions, quirk fixes Generic errors Generic errors
Quirk handling Auto-fix (assignee, parent) Documented workarounds Documented workarounds
Rate limiting Built-in retry No No
CLI Yes No No
License Apache 2.0 Proprietary MIT

Roadmap

Shipped: Jira full surface (v0.3.0) · Confluence core + markdown-to-storage with full CommonMark + GFM fidelity (v0.4.0, v0.5.2) · 1Password op:// token refs (v0.5.1) · metadata-only Confluence writes + preserve-on-omit body semantics (v0.5.2).

Next: confluence_delete_page, Confluence comments + attachments, Confluence integration-test path. Backlog in TODO.md.

Setup by Environment

Local (macOS / Linux)

# Recommended
uv tool install a2atlassian

# Or with pip
pip install a2atlassian

# CLI
a2atlassian login -p myproject --url https://mysite.atlassian.net --email me@co.com --token "$TOKEN"

# Or add as MCP server (see Quick Start)

CI / Automation

uv tool install a2atlassian

# Pre-configured — no login needed
uvx --from a2atlassian a2atlassian-mcp --register ci https://mysite.atlassian.net ci-user@co.com "${CI_ATLASSIAN_TOKEN}"

Development

make bootstrap   # Install deps + pnpm + git hooks
make check       # Lint + test + coverage-diff + security (full gate)
make test        # Tests with coverage
make lint        # agent-harness + jscpd + actionlint (never modifies files)
make fix         # Auto-fix + lint
make similar     # Advisory: report similarly-named functions/classes

Linters: ruff + ty (via agent-harness), yamllint, jscpd (copy-paste detection via pnpm), actionlint (GitHub Actions workflows). Pre-commit hooks run agent-harness fix + lint on every commit. Install pnpm and actionlint via brew install pnpm actionlint.

License

Apache 2.0


🏢 Agent-first Atlassian access since 2025.

Built by Denis Tomilin

Recommended MCP Servers

How it compares

Atlassian-focused MCP bridge with compact agent output, not a generic project-management skill pack.

FAQ

Who is a2atlassian for?

Developers and small teams using Jira and Confluence who want their coding agent to pull issues and pages without manual copy-paste.

When should I use a2atlassian?

Use it while building when you need ticket context, acceptance criteria, or Confluence specs inline with code changes.

How do I add a2atlassian to my agent?

Install the PyPI package a2atlassian, configure Atlassian credentials and site connection as required by the server, add stdio MCP config, and restart your client.

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