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Baron

Let your coding agent write to your work tracker — and keep the same flow when you change trackers. Baron is an open-source layer that turns issues, branches, PRs, CI runs, and deployments into one normalized contract, so your agent never learns a vendor's API, states, or column names.

Baron running the task-start then task-finish recipes through its normalized ports

The problem

AI coding agents bake one vendor's API and one team's process into prompts. The moment your issues live in Azure DevOps but your code is on GitHub, or your board columns aren't literally "To Do / Done", or you switch trackers next quarter — the prompts break, and the agent falls back to raw, vendor-specific tools. You've hardcoded vendor lock-in into the way you work.

Related MCP server: Jira - GitHub MCP Server

What Baron does

Plenty of tools let an agent read your tracker. Baron is about the other direction: writing — creating work items, moving them, cutting branches, opening and merging PRs — which is where an agent does damage when it guesses a vendor's state machine wrong.

The agent speaks one abstract vocabulary in terms of roles (backlog → ready → in_progress → in_review → done; blocking is an orthogonal flag, so a blocked item keeps the role the work is actually in), and Baron translates to each provider's real API, states, and quirks. You confirm that mapping once, at baron init, and it is committed to your repo as configuration — not re-guessed by the model on every call.

Each port binds to a provider independently, so issues on Azure DevOps, scm on GitHub, and notify on Slack is a normal setup rather than a special case.

What it looks like

You:  Start work on STORE-142.

Baron  ▸ runs the task-start recipe as a single call:
  ✓ Loaded STORE-142 "Add rate limiting to the login endpoint"  (type role: task)
  ✓ Checked it: not done, has a canonical branch, not assigned to someone else
  ✓ Branched feature/STORE-142 from the repo's default branch
  ✓ Moved STORE-142 → in_progress, assigned to you
  ✓ Commented on the item: "Started work — on branch feature/STORE-142."

That same prompt on Azure DevOps sets the work item state to Active; on GitHub it applies an in-progress label — because in_progress is a role, not a vendor state.

The checks matter as much as the actions: if the item is already done, belongs to someone else, or is a container that should never be branched, the run stops before anything is created. The branch name is derived by Baron from the item's type role, so every agent and every recipe derives the same name for the same item instead of inventing one.

Why it's different

  • Capability ports, not "a tracker." issues / scm / ci / deploy / notify, each bound to a provider independently — so a consumer mixes providers rather than betting on one vendor spanning everything.

  • Normalize, don't raw-proxy. New capabilities become first-class normalized ports; a clearly labeled provider-native escape hatch is the explicit last resort, never the default path.

  • Capability gaps are never silent. When a provider lacks something (say, native issue hierarchy), Baron either emulates it (e.g. labels), degrades with a warning, or errors loudly — decided by policy, never swallowed.

  • Workflows are recipes, not prompts. Multi-step flows (task-start, task-finish, task-land, ship) are declarative YAML executed as a single call, with guards that stop a run before it mutates anything. The order lives in the recipe rather than being improvised per run.

Quick start

Published to npm — no clone, no build. From inside your project:

# 1. Configure — one command. Auto-detects owner/repo from your git remote, offers to sign you in
#    through your browser (or paste a token instead), writes .baron/credentials (gitignored) +
#    .baron/policy.json (issues + scm bound).
npx -y @lonca/baron-cli@latest init --provider github      # or: --provider azure-devops

# 2. Check the policy against the live provider (drift → exit 1)
npx -y @lonca/baron-cli@latest doctor

# 3. Run a workflow recipe
npx -y @lonca/baron-cli@latest run --recipe task-start          # by name; or pass a path

On GitHub, step 1 opens the approval page and you confirm a short code — no permission list to read, no boxes to tick, no token to paste. Pasting a fine-grained token is still offered, because it is a narrower credential than any OAuth scope and an install that wants the tighter one should not have to fight the friendlier path to get it. Either way baron doctor verifies what the credential can actually do before you start work.

Or drive it from an agent — install the Claude Code plugin (MCP server + workflow skills in one):

/plugin marketplace add loncadev/baron
/plugin install baron@baron

See Getting started for the full walkthrough. Contributing to Baron itself? Run from source with pnpm baron … — see CONTRIBUTING.

Or wire the MCP server into your agent and call the tools directly across every port — baron_issue_write op=create, baron_scm_write op=pr_create, baron_ci_read op=runs, baron_deploy_read op=deployments, baron_notify_send, plus baron_recipe_run for whole workflows. In Claude Code, the plugin also ships per-recipe skills (/baron:task-start, /baron:ship). See docs/mcp.md.

The server is listed in the official MCP Registry as io.github.loncadev/baron, and runs as a container for anyone who would rather not have Node on the host — see docs/mcp.md.

New to it? The Azure DevOps setup walkthrough is copy-paste from scratch (PAT scopes, init → doctor → MCP, troubleshooting).

Providers

Provider

Ports

Azure DevOps

issues · scm · ci · deploy

GitHub

issues · scm · ci · deploy

Slack

notify

GitLab, Jira, and Linear are on the roadmap — adding one never changes how the agent talks to Baron, which is the whole point. Until they land, those names describe intent, not support.

Documentation

Guide

What it covers

Getting started

Install, prerequisites, first initdoctorrun.

Setup walkthrough — Azure DevOps

From-scratch, copy-paste setup on Azure DevOps + Claude Code.

Concepts

Ports, roles, capability gaps, the knowledge loop — the mental model.

Configuration

.baron/policy.json, role/type/gap maps, credentials.

CLI

baron init / doctor / run reference.

Recipes

Writing YAML recipes: ask / do / message, interpolation, the op table.

MCP server & plugin

The MCP tools and the Claude Code plugin.

Trying it with Claude Code

Hands-on: wire the MCP server to a real project + a verification checklist.

Providers

Which provider supports which port and capability.

Demo script

Ready-to-record 60-second demo (Claude Code or CLI).

The full design decision record is in ARCHITECTURE.md; the contributor working contract is CLAUDE.md, contribution terms are in CONTRIBUTING.md, and the publish playbook is RELEASING.md.

Status

v1 is built end-to-end: the issues, scm, ci, and deploy ports across Azure DevOps and GitHub plus notify via Slack, the config engine (baron init / doctor), a multi-port MCP server, the YAML recipe engine + baron run, the knowledge loop, and a Claude Code plugin. Every adapter passes a network-free conformance suite; the Azure DevOps ports are additionally live-validated against a real project.

Baron now also runs this repository — its issues, branches, and pull requests move through its own GitHub adapter. That is a working proof, not adoption: Baron is young and has not yet been put through a stack it did not grow up on. If you run it against yours, the resulting bug report is the most useful thing you could send. What is planned next, and what is deliberately out of scope, is in ROADMAP.md.

License

Open-core. The core, the P0 adapters (Azure DevOps, GitHub, Slack), the recipes, and the CLI/MCP server are licensed under Apache-2.0. Future commercial-tier features (SSO, secret-manager integrations, multi-team governance, audit) will ship under a separate commercial license — see ARCHITECTURE.md decision #20.

A
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quality - not tested
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maintenance - not tested

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