bernstein MCP工具

install in 30 seconds

pipx install bernstein
bernstein init
bernstein run -g "fix the failing test in tests/test_foo.py"

See installed integrations: bernstein integrations list --installed.

other install methods

curl -fsSL https://bernstein.run/install.sh | sh        # macOS / Linux one-liner
irm https://bernstein.run/install.ps1 | iex             # Windows PowerShell
pip install bernstein                                   # pip
uv tool install bernstein                               # uv
brew tap chernistry/tap && brew install bernstein       # Homebrew

See the full install matrix for dnf copr, npx, optional extras, and the wheelhouse path for air-gapped sites.

install

The one-liner scripts check for Python 3.12+, bootstrap pipx when it's missing, fix PATH for the current session, and install (or upgrade) bernstein. Script sources: install.sh · install.ps1.

use cases

• forward-deployed engineering: drop the crew onto a client repo when you arrive, take it with you when you leave.
• self-evolving projects: point Bernstein at its own repo and let it execute the backlog (this codebase is one).
• CI fleets: run a crew of agents in parallel on PRs, with per-agent credential scoping and signed audit trail.
• air-gapped deployment: install from a signed wheelhouse, run with --profile airgap to deny outbound by default. See Air-gap installation.

quick start

cd your-project
bernstein init                    # creates .sdd/ workspace + bernstein.yaml
bernstein -g "Add rate limiting"  # agents spawn, work in parallel, verify, exit
bernstein live                    # watch progress in the TUI dashboard
bernstein stop                    # graceful shutdown with drain

For multi-stage projects, define a YAML plan:

bernstein run plan.yaml           # skips LLM planning, goes straight to execution
bernstein run --dry-run plan.yaml # preview tasks and estimated cost

YAML workflow manifests (optional)

When bernstein run -g "<goal>" is too coarse-grained, bernstein workflow runs a declarative DAG of agent / command / loop nodes. Manifests are plain YAML, validated up-front, dispatched through the same AgentSpawner the rest of Bernstein uses.

bernstein workflow list                          # bundled + user-installed
bernstein workflow run idea-to-pr -g "Add JWT auth"
bernstein workflow init my-flow                  # scaffold a starter manifest
bernstein workflow validate path/to/flow.yaml

Stock workflows shipping in the wheel: idea-to-pr, refactor-with-tests, security-review, doc-update, dependency-bump, hot-fix. Loop nodes re-fire until a bash predicate exits 0. fresh_context: true mints a new agent session per iteration. Per-step CLI/model routing: docs/workflows/per-step-routing.md.

optional extras

Provider SDKs are optional so the base install stays lean.

Combine extras with brackets, e.g. pip install 'bernstein[openai,docker,s3]'.

Editor extensions: VS Marketplace · Open VSX

deterministic multi-agent CLI orchestration

website · docs · install · first run · glossary · limitations · sponsor

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Bernstein is a deterministic Python scheduler that runs a crew of CLI coding agents (Claude Code, Codex, Gemini CLI, and 40 more) against a single goal in parallel git worktrees, with an HMAC-signed audit chain over every step.

how it compares

Closest neighbours in this category live in docs/compare/README.md. What Bernstein does well is the auditability surface: HMAC-chained audit, signed agent cards, per-artefact lineage, air-gap deploy profile, plus the widest CLI adapter coverage.

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