Agent Lab

Run and test agentic systems in isolation. Agent Lab runs OpenCode in a Docker sandbox ("vacuum") with controlled settings and lets you observe how an agent behaves under varied system prompts, models, and task prompts — one run or many in parallel. It is built primarily to be called by agents (over MCP), and secondarily by humans (CLI).

• Vary system prompt / model / task prompt; run isolated, capture the full behavior trace.
• Two interfaces over one engine: MCP (stdio) and CLI — both agent-friendly.
• Three network modes and guaranteed sandbox teardown.

Prerequisites

1. Bun 1.x — bun --version
2. Docker running — docker --version
3. OpenCode configured on the host — a provider set up in ~/.config/opencode (auth in ~/.local/share/opencode). These are mounted read-only into each sandbox; nothing is baked into the image.

Install

Pick one. All three give you the agent-lab (CLI) and agent-lab-mcp (MCP server) commands. Docker (or the microsandbox runtime) and the sandbox image are separate prerequisites — see below.

npm (needs Node ≥ 22):

npm install -g agent-lab-opencode
# or run without installing:  npx -y agent-lab-opencode-mcp

Standalone binary (no Node/Bun required) — download for your platform from the latest release, e.g.:

curl -fsSL -o agent-lab https://github.com/ShutovKS/agent-lab-opencode/releases/latest/download/agent-lab-darwin-arm64
chmod +x agent-lab

From source (Bun):

bun install
bun link                                             # exposes `agent-lab` + `agent-lab-mcp` on PATH

Get the sandbox image (opencode serve) — either pull the published multi-arch image:

docker pull ghcr.io/shutovks/agent-lab-opencode:latest
docker tag ghcr.io/shutovks/agent-lab-opencode:latest agent-lab-opencode:latest

…or build it locally:

docker build -t agent-lab-opencode:latest docker/

The engine, CLI, and MCP server all run on the host (where Docker + your OpenCode config live). Experiments run inside isolated containers. Runs are persisted under runs/<runId>/ relative to the working directory the server/CLI is launched from.

Use from an agent — MCP (recommended)

Agent Lab exposes an MCP stdio server with four tools:

Tool	Arguments	Returns
run_experiment	systemPrompt, model, taskPrompt, image?, networkAllowlist?, networkMode?, timeoutMs?, concurrency?	runId + status
list_runs	—	known runs
get_run	runId	full run record + trace (steps, tool calls, tokens, output, git diff)
compare_runs	runIds[] (≥2)	structural behavior diff vs. the first (baseline)

Claude Code

This repo ships a .mcp.json, so opening the project in Claude Code registers the server automatically. To use it from any project after bun link:

{
  "mcpServers": {
    "agent-lab": {
      "command": "agent-lab-mcp"
    }
  }
}

OpenCode

In opencode.json (or ~/.config/opencode/opencode.jsonc):

{
  "mcp": {
    "agent-lab": {
      "type": "local",
      "command": ["agent-lab-mcp"]
    }
  }
}

Typical agent flow

1. run_experiment with prompt variant A → runId_A
2. run_experiment with prompt variant B → runId_B
3. compare_runs [runId_A, runId_B] → see which variant used fewer steps/tokens or a different tool sequence. Results come back as text and structuredContent (machine-readable).

Use from a shell — CLI

Agents with a shell tool (and humans) can call the CLI; every command prints parseable JSON.

agent-lab run --system "You are careful." --model cpa/glm-5.2 --task "Refactor the parser."
agent-lab run --config matrix.json --concurrency 3   # variation matrix, run in parallel
agent-lab run --from <runId>                          # replay a stored experiment
agent-lab list
agent-lab show <runId>
agent-lab compare <runId-a> <runId-b>

Config file (--config) is either a single definition or a variation matrix:

{
  "base": {
    "systemPrompt": "You are a concise agent.",
    "model": "cpa/glm-5.2",
    "taskPrompt": "placeholder",
    "sandbox": { "image": "agent-lab-opencode:latest", "networkAllowlist": ["cpa.funxyz.fun"], "timeoutMs": 120000 }
  },
  "variations": { "taskPrompt": ["Task A", "Task B"] }
}

Sandbox backends

Set backend on the sandbox options:

• docker (default) — one container per run; strong FS/PID/network isolation; the vacuum network mode is enforced with an in-container iptables allowlist. Requires Docker.
• microsandbox — a libkrun microVM per run, no Docker daemon. Same behavior behind the same contract (port publish, NetworkPolicy egress allowlist, guaranteed teardown). Requires the microsandbox runtime (curl -fsSL https://install.microsandbox.dev | sh) and a registry image (microsandbox pulls images from a registry, not a local Docker build), on macOS Apple Silicon or Linux+KVM. The SDK is lazy-loaded, so the Docker path never touches it.

Network modes

Set networkMode on the sandbox options:

• open (default) — bridge networking; the agent can reach its LLM. Fast, egress open.
• vacuum — strict deny-by-default egress via an in-container iptables allowlist (only DNS + the resolved allowlist hosts, e.g. the LLM endpoint + opencode infra). IPv6 fails closed.

What gets captured (RunTrace)

runId, experiment metadata, status (success/error/timeout), timings, ordered steps (assistant messages + tool calls with ok/error), tokenUsage, finalOutput (text + git diff), and error/partial when relevant.

More

• docs/LIVE_RUN.md — end-to-end live run walkthrough.
• docs/ — GRACE artifacts (requirements, technology, development plan, verification plan, knowledge graph). AGENTS.md — engineering protocol.

Known limitations

• Teardown is guaranteed on normal, error, timeout, and container-crash paths, but not if the host agent-lab process is hard-killed (SIGKILL). Containers are labeled agent-lab.sandbox=1 for cleanup: docker ps -aq --filter label=agent-lab.sandbox=1 | xargs docker rm -f.
• Vacuum: IPv6 is only reachable under a non-default docker IPv6 setup; DNS exfiltration to the configured resolver remains theoretically possible.