Give every git worktree its own isolated local world — ports, env, database, URLs — so a swarm of agents runs in parallel without collisions.
Project description
Binky
One isolated local world per git worktree — ports, env, database, URLs.
So a swarm of coding agents runs in parallel on one machine without anything colliding.
Docs · Quickstart · Adapters · Commands · For agents · How it works · Troubleshooting
docker-compose was built for one process at a time. Binky is built for fifteen at once.
Status: alpha. The core works end to end — worktree isolation, ports, adapters, supervision, reconciler, admission, proxy, HTTPS. The config format is stable; the CLI may still move.
The problem
You point three agents at the same repo. The second one runs pnpm dev and gets EADDRINUSE.
The third runs your migrations and drops the table the first was reading. You start hand-editing
.env files, and now you're the scheduler.
Binky is the scheduler. One binky up <branch> per agent, and each gets its own ports, its own
database, its own URLs — from the same committed config.
Install
Python 3.11+ and git, on Linux or Windows — the two platforms Binky is tested on for real. macOS isn't a supported target yet; a well-tested port would be a welcome contribution.
uv tool install binky # or: pipx install binky
binky --version
Or from a clone, to run the unreleased main or to hack on it:
git clone https://github.com/andreisilva1/binky && cd binky
uv tool install . # or: pipx install .
Adapters that need a driver ship as extras — installing Binky for Redis shouldn't pull boto3:
uv tool install "binky[postgres]" # or [redis], [mysql], [mongodb], [s3], [kafka]
uv tool install "binky[all-adapters]" # the whole matrix
Quickstart
Already have a docker-compose.yml? Start from it:
binky init # writes a binky.toml you can read and edit
binky check # validate it
Or write it by hand — this is the whole config:
[project]
name = "acme"
[services.web]
cmd = "pnpm dev --port ${self.port}"
url = "web" # → web.<worktree>.acme.localhost
depends_on = ["api"]
env = { API_URL = "${api.url}" }
[services.api]
cmd = "go run ./cmd/server"
url = "api" # asking for a URL is what asks for a port
depends_on = ["db"]
env = { DATABASE_URL = "${db.url}" }
[services.db]
adapter = "postgres" # a private database per worktree
admin_url = "${env.POSTGRES_ADMIN_URL}"
migrate = "make migrate"
seed = "make seed"
clone_from = "golden" # migrate+seed once, then copy per worktree
Then bring worktrees up in parallel:
$ binky up login-fix
api pid 16560 :4846
web pid 29732 :4504
✓ up: login-fix (2 service(s))
$ binky up checkout-v2
api pid 21768 :4137
web pid 46336 :4605
✓ up: checkout-v2 (2 service(s))
$ binky status
acme
checkout-v2 [running]
api :4137
web :4605
login-fix [running]
api :4846
web :4504
Two branches, four processes, four ports nobody chose by hand. Hand a worktree's coordinates to whoever needs them — a shell, an agent, a test run:
$ binky env login-fix --dotenv
WEB_URL=http://web.login-fix.acme.localhost
API_URL=http://api.login-fix.acme.localhost
And the rest of the lifecycle:
binky down login-fix # pause (keeps files + ports); `up` again is instant
binky remove login-fix # destroy it (refuses if there are uncommitted changes)
Nothing is hardcoded and nothing is discovered at runtime: every process boots already knowing the whole port map, its own and its dependencies'.
One rule to internalise. A service gets a port when it declares
urlorports— asking is explicit. A service with neither gets none, which is correct for a worker or a one-shot job, and a trap if you then write${self.port}in itscmd. Unknown tokens are left alone rather than blanked, so the literal${self.port}reaches the shell and the process dies on its own argument parsing.binky checkwarns when a service does this.
What it costs to run N worlds
The claim is that N isolated worlds shouldn't cost N times one world. Measured, not asserted —
benchmarks/worlds.py is in this repo and reproduces the table below (postgres:16, 200,000 rows
per world, Docker Desktop on Windows 11):
| worlds | RAM: a container each | RAM: Binky | time: a container each | time: Binky |
|---|---|---|---|---|
| 1 | 150 MiB | 174 MiB | 6s | 4s |
| 2 | 298 MiB | 182 MiB | 11s | 6s |
| 4 | 596 MiB | 228 MiB | 20s | 10s |
| 8 | 1197 MiB | 295 MiB | 40s | 16s |
The 8th world costs +150 MiB and +4.8s as its own container, or +17 MiB and +1.7s under Binky.
Read the first row too. At one world Binky is behind — it pays for a server plus a golden
template nobody is using yet, and only earns that back on the second. And disk is not a win:
CREATE DATABASE ... TEMPLATE is a file copy, not copy-on-write, so every world is still a full
copy of the rows. What Binky removes is the server per world, not the bytes per world. It also
doesn't make your own app processes cheaper — one dev server per worktree costs the same either way.
python benchmarks/worlds.py --sweep 1,2,4,8 --rows 200000
When you don't need Binky
Worth saying plainly, because the first row of that table already says it:
- One branch at a time. If you never have two worlds up at once, Binky is a daemon and a config file you didn't need. Use it when the second agent shows up.
- Everything already runs in containers, and that's fine. Binky's win is removing the server per world. If your compose stack is small enough that N copies fit comfortably, there's nothing to reclaim.
- You need real isolation, not local isolation. Binky runs your commands as you, on your machine. It is not a sandbox — see Security.
Adapters
An adapter carves an isolated slice of one shared server — a database, a key prefix, a bucket — instead of running one server per worktree. 16 names, 10 implementations, every one exercised against a real server in CI.
| slice | adapters |
|---|---|
| a database | postgres · mysql · mariadb · percona · mongodb · clickhouse |
| a key prefix | redis · valkey |
| a bucket / prefix | s3 · minio |
| a vhost / topic prefix | rabbitmq · kafka · redpanda |
| a collection | qdrant |
| an index prefix | elasticsearch · opensearch |
Protocol-compatible names share one implementation rather than a copy of it — valkey is the Redis
adapter, percona is the MySQL one, opensearch is the Elasticsearch one.
clone_from: pay for migrate+seed once
With clone_from, the first binky up builds a golden template — provision, migrate, seed —
and every worktree after that is a copy of it. The template is keyed by a hash of your migrate and
seed commands, so changing either rebuilds it automatically.
Supported where the server can copy a slice server-side (postgres, mysql, mariadb, percona,
mongodb). Where it isn't, or where a clone fails on something environmental — a client binary too
old to authenticate, a missing grant — Binky falls back to provision+migrate+seed for that
worktree and logs clone_fallback. Correctness never depends on cloning; only speed does.
One sharp edge worth knowing: the hash covers the migrate and seed commands, not the files they
call. Editing a script those commands run does not rebuild the template — delete its marker under
~/.binky/golden/ to force one.
Writing your own
Two tiers, one contract. Both implement the same four verbs:
| verb | does |
|---|---|
provision(slice) |
create the slice (CREATE DATABASE ...) |
resolve(slice) |
return its address → ${db.url} |
teardown(slice) |
destroy it |
capabilities() |
what it supports, e.g. {"clone": true} |
In-process adapters are Python classes in this repo, discovered by name. External adapters
are executables in any language, discovered as binky-adapter-<name> on PATH and driven over a
one-shot subprocess + JSON protocol:
$ binky-adapter-filestore provision <<< '{"slice": "acme_login-fix", "config": {}}'
{"ok": true}
$ binky-adapter-filestore resolve <<< '{"slice": "acme_login-fix", "config": {}}'
{"ok": true, "address": "file:///tmp/binky-filestore/acme_login-fix"}
Python authors get the protocol for free — binky.adapter_sdk.run() bridges a normal adapter class
to it. See examples/adapters/filestore.py for a complete,
dependency-free one in 30 lines.
Commands
| Command | What it does |
|---|---|
binky init [dir] [--force] |
Write a starting binky.toml from docker-compose.yml + .env |
binky check [path] |
Validate a binky.toml and flag footguns |
binky up <name> [--group g] |
Create/use the branch's worktree, allocate ports, provision resources, start services |
binky reload <name> [--group g] |
Restart in place — stop, then bring back up on the same ports and data |
binky down <name> |
Stop the worktree's processes (keeps its files and ports) |
binky remove <name> [--force] |
Destroy the worktree — stop, drop its slices, remove its files |
binky status [.] |
List worktrees (grouped by project); . = current project only |
binky env <name> [--dotenv] |
Print a worktree's exposed coordinates, for you or an agent |
binky curl <name> <service> [path] |
Call a service through the proxy with the Host header filled in (-X/-d/-H/-i/-f) |
binky verify <name> |
Run the project's agents.verify checks; exits non-zero on failure |
binky logs <name> |
Print a worktree's captured service logs |
binky gc |
Sweep orphaned adapter slices a crash left half-provisioned |
binky config |
Show the machine-global settings (RAM/disk reserves, proxy ports) |
binky reserve [--ram %] [--disk gb] |
Set how much RAM/disk Binky permanently keeps free |
binky port [--proxy p] [--https p] |
Set the proxy/HTTPS ports |
binky dashboard |
Live TUI of every worktree |
binky doctor |
Diagnose the install and daemon; exits non-zero if something is wrong |
binky metrics |
Point-in-time daemon metrics as JSON |
binky mcp |
Run the MCP server so agents can call Binky's verbs as tools |
binky daemon start|stop|status |
Manage the background daemon |
For agents
binky mcp speaks MCP over stdio, exposing up, down, status, env and verify — the same
verbs the CLI calls, against the same daemon.
In Claude Code, one line wires it up:
claude mcp add binky -- binky mcp
Any other client that speaks the protocol takes the same stdio server as a config block — the same one everywhere, only the file differs:
{ "mcpServers": { "binky": { "command": "binky", "args": ["mcp"] } } }
To run it with nothing installed, hand it to uvx instead — claude mcp add binky -- uvx --from "binky[mcp]" binky mcp, or as a block, "command": "uvx", "args": ["--from", "binky[mcp]", "binky", "mcp"]. For a project whose worktrees provision adapter slices, add those extras too, e.g.
binky[mcp,postgres] (or binky[mcp,all-adapters] for the whole matrix).
For the tool list and an agent-oriented walkthrough, see AGENTS.md.
How it works
A single machine-global daemon sits between your worktrees and the machine:
flowchart TB
CLI["agents · CLI · MCP"] -->|"up · down · status"| D(("binky daemon<br/>machine-global"))
D --> ADM{"admission<br/>RAM · disk · max_parallel"}
ADM -.->|"no room → queue / suspend"| Q["waiting"]
ADM -->|"admit"| W["worktree<br/>git worktree per name"]
W --> P["ports<br/>whole map before start"]
P --> R["adapters<br/>isolated slice per worktree"]
R --> S["supervisor<br/>depends_on · health · logs"]
S --> X["proxy<br/>svc.worktree.domain → port"]
D -.->|"reads · writes"| ST[("~/.binky<br/>SQLite + settings")]
- Worktree — creates/uses a git worktree per name.
- Ports — a global allocator assigns every process a port before anything starts and injects
the whole map, so nothing collides (
${self.port},${api.url}, …). - Resources — adapters carve an isolated slice per worktree and tear it down on remove.
- Supervision — starts services in
depends_onorder, waits for health, captures logs. - Proxy — routes
<service>.<worktree>.<domain>to the right port (WebSockets/HMR included). Sethttps = trueand Binky fronts it with Caddy for TLS via a local CA, when Caddy is on PATH. - Admission — a FIFO queue that only starts a worktree when the machine has room: fewer than
max_parallelrunning and enough free RAM (a percentage kept in reserve) and enough free disk (a fixed GB headroom). If a running swarm later crosses the RAM reserve, the daemon suspends the newest worktree to relieve pressure and resumes it — in fairness order — once room returns. Tune the reserves withbinky reserve; see them withbinky config.
State lives in ~/.binky/ (a SQLite registry plus a settings store, migrated in place across
upgrades). Nothing runs in the cloud, and Binky never phones home.
Examples
- examples/hello — the smallest possible project.
- examples/rag — vector search where each worktree gets its own embedded corpus.
The case where sharing a database actually hurts: two agents re-indexing, one
TRUNCATE. - examples/adapters/filestore.py — an external adapter, complete.
Security
Binky runs your commands on your machine as you. It is a developer tool for a
single-user workstation, not a multi-tenant sandbox — a binky.toml is as trusted as a Makefile,
and binky up on a repo you don't trust is make on a repo you don't trust. The threat model and
what's explicitly out of scope are written down in SECURITY.md.
The one rule worth repeating here: never put a credential inline in a committed binky.toml.
Use ${env.NAME} or an env_file. binky check warns when you do, and binky init never writes
one.
Something not working?
TROUBLESHOOTING.md covers the cases that actually come up — a port held from
outside, a dev server ignoring $PORT, a stale golden template, *.localhost not resolving. Start
with binky doctor.
Development
python -m venv .venv && . .venv/bin/activate # or .venv\Scripts\activate on Windows
pip install -e ".[dev,all-adapters]"
pytest
ruff check src tests examples benchmarks
Adapter integration tests skip unless you point them at a real server —
BINKY_TEST_PG, BINKY_TEST_REDIS, BINKY_TEST_MYSQL, BINKY_TEST_MONGO, BINKY_TEST_S3,
BINKY_TEST_RABBITMQ, BINKY_TEST_KAFKA, BINKY_TEST_QDRANT, BINKY_TEST_CLICKHOUSE,
BINKY_TEST_ELASTICSEARCH. CI provides all of them.
Contributing
Bug reports, new adapters, and PRs are welcome — see CONTRIBUTING.md to get set up, and ARCHITECTURE.md for a map of the internals.
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