WorkerLane

Harness-agnostic agent coworkers for any agent runtime. One package that wires team agents, approvals, memory, traces, and handoff contracts into whatever harness you already use.

Part of Talocode — open tools people trust, hosted power behind them.

What it is

AI agents are great at running tasks. The hard part is everything around them: who can run what, what gets approved, what happened last session, and proving it after the fact. WorkerLane bundles those pieces into one package that works with any agent harness — no runtime brand loyalty, no side to pick.

• AI coworkers — create agents with a name and role, queue tasks, gate destructive work behind approvals

• Agent-human handoffs — validate and repair step-to-step payloads against schema contracts so runs never silently drift

• Full data recording, owned by you — trace spans with cost and status, plus durable memory that persists across sessions. Everything is stored locally in ~/.workerlane unless you opt into the hosted path

• Computer use — run screenlane mcp (@talocode/screenlane) alongside workerlane mcp to add screen capture, dictate, and command tools to the same harness

• Works with any harness — expose the whole bundle as MCP tools and connect any MCP-compatible agent

Related MCP server: MCP Agent Orchestrator

Why it exists

The catalog is strong but fragmented — agents, traces, memory, handoffs each ship separately. WorkerLane removes the assembly. One install, one surface, all the pieces wired together. It is positioned as a capability layer above the harness, exactly where compounding value lives.

Install

npm install -g @talocode/workerlane

or

pip install workerlane

No Office, no runtime, no cloud required. Local engine runs entirely on your machine.

Quickstart (CLI)

# start the MCP server — connect any harness to it
workerlane mcp

# create a coworker
workerlane agent create --name "qa-bot" --role "reviews every PR before merge"

# queue a task, gated behind an approval
workerlane agent run --agent <ID> --task "audit the auth flow" --approve

# save and recall memory across sessions
workerlane memory remember --text "deploy is Fridays, freeze after 4pm" --tags ops,deploy
workerlane memory recall --query "deploy"

# start a trace run
workerlane trace start --name "release-check"

Quickstart (MCP — any harness)

{
  "mcp": {
    "workerlane": {
      "type": "local",
      "command": ["workerlane", "mcp"]
    }
  }
}

Once connected, these tools are available to any MCP-compatible agent:

Computer use (sibling server): install @talocode/screenlane, then add a second MCP entry:

{
  "mcp": {
    "screenlane": {
      "type": "local",
      "command": ["screenlane", "mcp"]
    }
  }
}

Exposes screenlane_capture, screenlane_dictate, screenlane_command, screenlane_send, screenlane_doctor to the same harness. Hosted browser automation is available via Agent Browser on Talocode Cloud (/v1/agent-browser/*).

SDK

import { createAgent, createAgentRun, approveAgentRun, validateHandoff, remember, recall, createTraceRun, startTraceSpan } from '@talocode/workerlane'

const bot = createAgent({ name: 'qa-bot', role: 'reviews every PR before merge' })

const run = createAgentRun({ agentId: bot.id, task: 'audit the auth flow', requireApproval: true })
// → a human approves it before it runs
approveAgentRun(run.id, true)

const r = validateHandoff({
  value: { intent: 'ship', confidence: 0.9 },
  schema: { type: 'object', required: ['intent', 'confidence'], properties: { intent: { type: 'string' }, confidence: { type: 'number' } } },
})

remember('deploy is Fridays, freeze after 4pm', ['ops', 'deploy'])
const facts = recall('deploy')

const trace = createTraceRun('release-check')
const span = startTraceSpan(trace.id, 'verify', 'tool')

Data & ownership

• Everything is local-first. State lives in ~/.workerlane/ (override with WORKERLANE_DIR).

• agents.json — agent registry + run audit trail with approval decisions

• memory.json — durable memory

• traces.json — span receipts with cost + status

• Export or delete these files any time — the data is yours.

Hosted path

For teams that want managed power, WorkerLane is available on Talocode Cloud under /v1/workerlane/* with Stacklane billing. The local engine is always free.

Related packages

• @talocode/worklane · pip install worklane-ai

• @talocode/memorylane · pip install memorylane-ai

• @talocode/handofflane

• @talocode/tracelane

• @talocode/agent-browser (hosted computer use)

Talocode ecosystem

More: github.com/talocode · talocode.site · docs.talocode.site

License

MIT © Talocode