Shep
Open-source, local-first orchestrator that runs parallel AI coding agents in isolated git worktrees, from a one-line idea to a merged pull request.
Shep earns a RAC recommendation for teams already committed to AI coding agents. Git-worktree isolation per feature genuinely prevents the file collisions and port conflicts that plague parallel agent runs, and the CI watch-and-fix loop (up to three retries) closes the gap from code to merged PR. Because it is MIT-licensed and local-first with state in ~/.shep/ SQLite, you pay nothing beyond the agent subscriptions you already have, and you can swap Claude Code, Cursor CLI, or Gemini CLI per feature. The tradeoffs are real: you need Node 22+, GitHub CLI, and CLI fluency, and the dashboard is localhost:4050 rather than a hosted team surface. If you want a managed cloud orchestrator with
Verified 2d ago · liveness 70/100 · cite: rightaichoice.com/tools/shep
- Development teams already using AI coding agents
- Solo developers comfortable with CLI, git, and worktrees
- Teams with CI/CD pipelines wanting automated fix loops
- Open-source contributors wanting a free, local-first orchestration tool
- Non-developers without coding experience or CLI familiarity
- Teams not using AI coding agents
- Users needing hosted, managed infrastructure or a shared cloud dashboard
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Skip Shep if you have not adopted a CLI coding agent (Claude Code, Cursor CLI, or Gemini CLI) or are not comfortable with git worktrees and the terminal — Shep orchestrates agents you already run, it does not replace having one.
Shep itself is free and MIT-licensed, but you must bring a paid agent subscription — Claude Code, Cursor, or Gemini — and that recurring cost is entirely outside Shep.
Shep is free and MIT-licensed — the cheapest way to orchestrate parallel coding agents if you already pay for Claude Code, Cursor, or Gemini. Your real cost is that agent subscription, which you keep. Versus managed orchestrators baked into Cursor or Sourcegraph, Shep is $0 to Shep itself and trades paid managed infrastructure for a self-hosted localhost dashboard you run on Node 22+.
In short
Shep — Open-source, local-first orchestrator that runs parallel AI coding agents in isolated git worktrees, from a one-line idea to a merged pull request. Best for Development teams already using AI coding agents, Solo developers comfortable with CLI, git, and worktrees, Teams with CI/CD pipelines wanting automated fix loops. Free to use.
What people actually say about Shep — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
31 mentions across 3 sources (Hacker News, Product Hunt, Lemmy) · researched Jul 3, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Agent-agnostic – works with any CLI-based AI coding agent.
- +Parallel execution enables faster feature development across multiple agents.
- +Git worktree isolation prevents file collisions and port conflicts.
- +Open-source (MIT) and free, no vendor lock-in.
- +Local-first architecture: all data stays in user's filesystem.
- −Almost no community feedback or real-world usage evidence.
- −Requires Node 22+ – not yet standard in many development setups.
- −Need separate paid subscriptions for underlying AI agents.
- −Name collision with a travel expense tool causes confusion.
- −Documentation and onboarding may be incomplete for new users.
- • Requires paid AI agent subscriptions (e.g., Claude Code, Cursor) – not included
Viability Score
How well maintained and how widely used is Shep? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Parallel agent orchestration — launch three, five, or ten features at once
- Git worktree isolation: one worktree and branch per feature
- Automatic branch and worktree creation from a one-line description
- Spec-driven mode (`--no-fast`) with YAML requirements and approval gates
- Agent-agnostic executor: Claude Code, Cursor CLI, Gemini CLI, any CLI
- CI watch with auto-fix — agent reads logs and pushes fixes, up to 3 retries, configurable
- Draft PR auto-push and real PR merge via GitHub CLI
- Optional `--allow-merge` flag for automated PR merging
- Local web dashboard at localhost:4050 with live repo/feature graph
- Full CLI parity: `shep feat new`, `shep run`, `shep implement`
- Multi-repo fleet commands from one dashboard or terminal
- SQLite state stored in ~/.shep/
- No account, no usage meter, no Shep servers
- MIT-licensed, local-first, cross-platform (Windows, macOS, Linux)
- Runs via `npx @shepai/cli` on Node 22+
About Shep
Shep is a free, MIT-licensed, local-first control plane for developers who already use AI coding agents. Instead of running one feature at a time, you describe a feature in a sentence (or run `shep feat new`) and Shep creates a dedicated git worktree and branch. In spec-driven mode (`--no-fast`) it drafts requirements, research, and a plan as YAML and pauses at approval gates before any code is written. Each feature then gets its own agent session — Claude Code, Cursor CLI, Gemini CLI, or any CLI that runs in a terminal — and Shep commits, pushes, opens a draft pull request, watches CI, and pushes fixes (up to three retries, configurable) when checks fail. You keep your main checkout clean and review the final diff; Shep only auto-merges if you pass `--allow-merge`. Everything is orchestrated from a local dashboard at localhost:4050 that renders a live graph of every repo and feature, or from full CLI parity (`shep feat new`, `shep run`, `shep implement`). State lives in SQLite at ~/.shep/, with no Shep servers, no account, and no usage meter. It runs anywhere Node 22+ runs (Windows, macOS, Linux) and requires GitHub CLI configured for the PR workflow. It is built for developers and small teams comfortable with git, worktrees, and the terminal who want to parallelize feature work without manually juggling sessions.
Behind the Verdict
Shep's core insight is that most parallel-agent chaos is a git problem, not a model problem. By giving every feature its own worktree on its own branch, it eliminates clobbered files, port collisions, and half-finished edits bleeding between tasks — a failure mode anyone who has run two Claude Code sessions in one checkout will recognize immediately. The pipeline is opinionated in a useful way: describe, optionally spec, run agents, review, merge. Spec-driven mode is the standout for complex work, drafting requirements, research, and a task plan as YAML and pausing at gates you approve before code lands; the `--no-fast` flag is the switch. The CI watch loop reads your pipeline logs and has the agent push a fix, up to three retries, configurable — which is the difference between an agent 'finishing' and a PR actually going green. Agent-agnosticism is the second pillar. Agents run through a generic executor interface, and the docs list Claude Code, Cursor CLI, Gemini CLI, and any CLI that runs in a terminal, swappable per feature and per repo. That is meaningfully different from Cursor's built-in agent orchestration, which keeps you inside one vendor's loop. It is also a hedge: as agent CLIs churn, Shep's value stays in the orchestration layer rather than in any one model. The honesty section: Shep is not a coding agent and does not ship a model. You bring your own subscription, plus Node 22+ and a configured GitHub CLI. PRs open as drafts on named branches and merge manually unless you flag `--allow-merge`. The dashboard is a single localhost:4050 instance, not a hosted multi-user surface, so distributed teams won't get a shared cloud view. The state store is local — good for privacy, less good if you want a machine-independent record. For a solo dev or small team already paying for Claude Code or Cursor, Shep's cost is zero and its ceiling is high; for teams that want managed infrastructure and no CLI, look elsewhere first.
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Real-world workflow fit
Concrete scenarios for the personas Shep actually fits — and what changes day-one when you adopt it.
You run `shep feat new "add cursor pagination to GET /todos" --push --pr` for three separate features. Shep cuts three worktrees and branches, spins up a Claude Code session per feature, commits, pushes, and opens draft PRs — while you keep coding on main.
Outcome: Three features move in parallel with zero file conflicts, and you review three draft PRs from the localhost:4050 graph instead of babysitting sessions.
You use fleet commands to spin up feature work across repos, each feature isolated in its own worktree with a Gemini CLI session. When CI fails, Shep reads the logs and pushes a fix, up to three retries.
Outcome: Pipeline failures get auto-fixed without a human rerunning the agent, and PRs land as normal pull requests into your existing review process.
You run with spec-driven mode (`--no-fast`) so Shep drafts requirements, research, and a task plan as YAML. You approve at the gate before any code is written, then agents implement task by task.
Outcome: Complex changes get a reviewable plan up front rather than an agent improvising, and only tasks you approved move to implementation.
Use Cases
- Run multiple features in parallel on separate worktrees, each with its own Claude Code, Cursor, or Gemini session, to cut feature delivery time.
- Automate the full cycle from a one-line feature description to a merged pull request, including CI fix loops.
- Have the agent draft a YAML spec with requirements and approval gates for complex changes, gating implementation until you approve.
- Watch CI after every push and let Shep push fixes (up to 3 retries) when a pipeline fails, instead of rerunning the agent manually.
- Orchestrate feature work across multiple repositories at once using fleet commands from one dashboard or terminal.
- Swap between Claude Code, Cursor CLI, and Gemini CLI per feature or repo to avoid vendor lock-in.
- Keep your main checkout clean while agents work in isolated worktrees so you can keep coding without conflicts.
Models Under the Hood
as of 2026-10-11
Limitations
- Shep is not a standalone AI model — it orchestrates external agent CLIs (Claude Code, Cursor CLI, Gemini CLI, or any CLI that runs in a terminal) that you must already have and pay for separately.
- It is local-first, requiring Node 22+, and runs its dashboard at localhost:4050 rather than as a hosted cloud service.
- A configured GitHub CLI is required for the PR workflow.
- PRs open as draft pull requests on named branches and merge manually unless you pass `--allow-merge`.
- The dashboard is a single local instance, so there is no shared multi-user team view.
as of 2026-10-08
Verification history
We have re-verified Shep 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Shep tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Solo developers and small teams already paying for Claude Code, Cursor, or Gemini who want parallel agent orchestration at zero Shep cost.
What this tier adds
Starting tier: $0/mo, MIT-licensed, local-first, unlimited parallel agents, worktree isolation, CI auto-fix, and the localhost:4050 dashboard — you bring your own agent subscription.
Where the pricing makes sense
The company stage and team size where Shep's pricing actually pencils out — and where peers do it cheaper.
Shep is free and MIT-licensed — the cheapest way to orchestrate parallel coding agents if you already pay for Claude Code, Cursor, or Gemini. Your real cost is that agent subscription, which you keep. Versus managed orchestrators baked into Cursor or Sourcegraph, Shep is $0 to Shep itself and trades paid managed infrastructure for a self-hosted localhost dashboard you run on Node 22+.
Setup time & first value
How long it actually takes to get something useful out of Shep — broken out by persona, not the marketing-page minute.
Solo dev already using Claude Code or Cursor: roughly 5–10 minutes — run `npx @shepai/cli`, ensure Node 22+ and GitHub CLI are configured, and ship a first feature. Team lead orchestrating multiple repos: 30–60 minutes to set agent credentials, branch conventions, and CI retry settings. Expect longer if your environment needs Node 22+ installed or GitHub CLI authenticated.
Switching to or from Shep
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From manual Claude Code / Cursor sessions in one checkout: run `npx @shepai/cli`, then `shep feat new` per feature so each gets its own worktree and branch, eliminating file collisions.
- →From Cursor's built-in agent orchestration: install Shep and point it at the same agent CLIs — you keep your subscriptions and gain worktree isolation plus CI auto-fix.
- →From hand-rolled git worktree scripts: replace them with `shep run` and fleet commands for managed worktree creation, commit, push, and PR opening.
- →From a single-agent CI fix loop: enable CI watch and auto-fix in Shep so failing pipelines trigger up to three agent retries automatically.
- ↗To a managed cloud agent orchestrator: export the worktrees from ~/.shep/, since Shep stores all state locally and there is no hosted migration path.
- ↗To a single vendor's native orchestration (e.g., Cursor): drop Shep's CLI and dashboard, keep your agent subscriptions, but lose cross-agent flexibility and worktree fleet commands.
- ↗To manual git workflows: Shep's per-feature branches are standard, so existing worktrees and draft PRs remain valid git artifacts you can manage by hand.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Shep”, and we withheld 6: 6 could not be judged, because “Shep” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Shep.
Official links
Tools that pair well with Shep
Common stack mates teams adopt alongside Shep, with the specific reason each pairing earns its keep.
GitHub Copilot
GitHub Copilot is an AI coding agent that completes code, reviews pull requests, and runs Copilot, Claude, and Codex agents inside GitHub
OpenHands
OpenHands runs autonomous coding agents that review PRs, fix CI, and triage incidents on your own triggers and models.
Qodo
AI code review and governance layer that enforces your standards on every pull request and gives coding agents a quality counterpart.
Featured Head-to-Head Comparisons
Shep vs Locus Robotics
These are not competitors — nobody is choosing between warehouse robots and a coding-agent CLI. Locus Robotics is a capital-and-contract decision for fulfillment operations that need AMRs, LocusONE orchestration, and WMS integration (SAP EWM, Manhattan, Blue Yonder, Oracle, Dynamics 365, NetSuite, Infor, Körber); pricing is quote-based via RaaS, so the buyer's real work is a pilot and ROI model. Shep is a free, MIT-licensed local tool: install it, describe a feature, and it creates a git worktree and branch, runs Claude Code/Cursor CLI/Gemini CLI, pushes a draft PR, watches CI, and retries fixes up to three times. If your problem is picking throughput, talk to Locus; if it's agent sprawl in git, run Shep.
Shep vs Presto Voice
Presto Voice and Shep serve entirely different domains: Presto is a drive-thru voice AI for QSR chains, while Shep orchestrates AI coding agents for developers. Choose Presto if you run multiple drive-thru locations and want to boost revenue via upselling. Choose Shep if you use AI coding agents and need to run them in parallel with CI auto-fix.
Shep vs Truleo
Choose Truleo if you run a law enforcement agency and need to surface leads from siloed data sources like RMS, CAD, jail calls, and body cameras. Choose Shep if you're a developer team that wants to parallelize AI coding agents and automate CI fixes for faster feature delivery. They serve entirely different domains, so the decision depends on your role—detective or developer.
Alternatives to Shep
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GitHub Copilot is an AI coding agent that completes code, reviews pull requests, and runs Copilot, Claude, and Codex agents inside GitHub
Frequently Asked Questions
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