pi-subagent
This server turns the Pi CLI into a programmable coding sub-agent that any MCP host can use to delegate tasks, track sessions, harvest results, and abort runs.
Delegate tasks to isolated
pi -pchild processes, with default async mode to avoid tool-call timeouts.Harvest results with
pi_status, using long-polling to wait for a run to finish.Make scheduling decisions via
pi_plan: whether to delegate, how many sessions to fan out, and whether to run sync or async.Manage sessions: list sessions (optionally filtered by cwd), inspect a session snapshot, and fork a session to try an alternative path.
Kill/abort any running
pirun by run ID.Works as a standard MCP server over stdio, so it can be loaded by ZCode, Claude Code, Cursor, or any MCP client.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@pi-subagentDelegate implementing user authentication"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
pi-subagent
Turn the Pi CLI (
@earendil-works/pi-coding-agent) into a programmable coding sub-agent that any MCP host (ZCode, Claude Code, Cursor, …) can delegate tasks to, track sessions, and kill processes.
pi-subagent is a thin MCP server that wraps pi -p --mode json into 7 structured tools: delegate tasks, harvest results, make scheduling decisions, manage named sessions, and abort runs. Process-isolated, fully session-based, sync/async dual-mode.
Why
Pi is a minimal terminal coding agent. Rather than teaching Pi methodology, this project treats Pi as a delegatable worker: a host agent (ZCode / Claude Code) decides when to delegate, fires off a self-contained task, and harvests the result. One Pi process = one isolated sub-agent run.
Process isolation — each delegation spawns one
pi -pchild process. A Pi crash only affects that run.Fully session-based — every task binds to a named session (e.g.
feat-auth); subsequent calls auto-continue.Sync / async — defaults to
async(avoids host tool-call timeouts); harvest withpi_statuslong-poll.Schedulable —
pi_planis a pure 5-stage decision function (reject / capacity / reuse / modify / mode), fully unit-tested.Universal MCP — any standard MCP client can load it.
Related MCP server: cursor-agent-bridge
Architecture
┌─────────────────────────────────────────────────────────────┐
│ MCP Host (ZCode / Claude Code / Pi / Cursor …) │
└───────────────────────────┬─────────────────────────────────┘
│ MCP (JSON-RPC over stdio)
▼
┌─────────────────────────────────────────────────────────────┐
│ pi-subagent-server (Node/TS) │
│ ┌────────────┐ ┌──────────────┐ ┌────────────────────┐ │
│ │ Tool layer │ │ Session │ │ Pi runner │ │
│ │ (7 tools) │─▶│ registry │─▶│ (spawn pi -p) │ │
│ │ + plan() │ │ + persist │ │ parse agent_end │ │
│ └─────┬──────┘ │ + _snapshot │ │ + tool_execution │ │
│ │ └──────────────┘ └─────────┬──────────┘ │
│ │ ┌────────▼─────────┐ │
│ └───────────────────────────│ Run registry │ │
│ (kill) │ + process-table │ │
│ └──────────────────┘ │
└─────────────────────────────────────────────────────────────┘
│ child_process.spawn({ cwd })
▼
┌─────────────────────┐
│ pi CLI (0.77+) │
└─────────────────────┘Three layers with clear boundaries: Tool layer (MCP schema + plan() pure function) / Session registry (state + persistence + redaction) / Runner (spawn pi, parse NDJSON, process table).
Tools
Tool | Purpose |
| Decide: should-delegate, sync/async, how many sessions |
| Dispatch a task (default async; new sessions wait for handshake) |
| Harvest a run's result (long-poll) |
| List sessions (omit |
| Inspect one session |
| Branch a session to try another path |
| Abort a run |
| Create a multi-stage task (host writes |
| Dispatch a domain review of the plan (harvest via |
| Run one stage: sync (wait for outcome) or async (returns runId) |
| Harvest an async stage run; auto-judges and re-dispatches (max 3), else manual |
| List tasks (filter by taskId / status) |
Review loop: after
pi_task_plan, harvest withpi_status(runId). When the run finishes, the server detects it is a review run, parses_plan-reviewed.md, and storesplanVerdict/planReviewedPathon the task. Stage prompts automatically include the reviewed plan and the output files of passed dependency stages.
Async stages: pass
mode: "async"topi_task_stage_runto avoid blocking a tool call for the full run (recommended when the MCP host enforces a short tool timeout). Harvest withpi_task_stage_collect(taskId, stageId). Failed attempts re-dispatch under a fresh session name to avoid history contamination; after 3 failures the stage goesmanualwith a decision panel (retry_with_new_hintis supported viapromptHintOverride).
Restart recovery: re-running
pi_task_createwith the sametaskIdmerges instead of conflicting. Stages whose output file already exists and passes validation are markedpassedautomatically, so interrupted tasks resume without hand-editingtasks.json.
Session model
Each session has a human-readable name + Pi's UUID +
cwd+goal.First
pi_delegatecreates the session (goalrequired); later calls auto-continue.The registry persists to
~/.pi-subagent/registry.json(atomic write; on restart, interruptedrunningrecords are corrected toerror).Concurrency cap: 4 running runs; a single session is never run concurrently.
Tasks persist to
~/.pi-subagent/tasks.json(atomic write; running stages are corrected tofailed(interrupted_by_restart)on restart).
Install
git clone <this-repo> && cd pi-subagent
npm installPrerequisite: the pi CLI is installed (npm i -g @earendil-works/pi-coding-agent) and on PATH.
Configure an MCP host
Add to your MCP client config:
{
"mcpServers": {
"pi-subagent": {
"command": "npx",
"args": ["tsx", "/abs/path/to/pi-subagent/src/server.ts"]
}
}
}Optional env vars:
PI_SUBAGENT_REGISTRY— registry path (default~/.pi-subagent/registry.json)PI_BIN— override the pi executable (used by tests)
Test
npm test # full suite (140 tests)
npm run test:fast # dot reporterTests use a fake pi (test/fixtures/fake-pi.sh) and cover: async/sync, timeout, kill, session-create-failure, multi-waiter, progress cap, scheduling rules (table-driven + 100-iteration property tests), registry persistence, redaction, etc.
Project layout
src/
├── types.ts # all shared types + error codes
├── errors.ts # ToolError helpers
├── runner/ # parse.ts, argv.ts, spawn.ts, process-table.ts
├── registry/ # session.ts, run.ts, persist.ts, redact.ts
├── scheduler/ # keywords.ts, plan.ts (5-stage pure function)
├── tools/ # delegate, status, plan-tool, session, kill
└── server.ts # MCP entry (stdio)
skills/pi-subagent/ # SKILL.md + delegation-patterns (strategy layer)
test/ # fixtures/ + *.test.ts
docs/ # design.md (spec) + implementation-plan.mdDesign & process
This project went through collaborative design + 4 rounds of external review before implementation. The spec and plan are committed under docs/:
docs/design.md— full design spec (architecture, tool contracts, error handling, scheduler rules, testing strategy). Every contract is traceable to a review note (R1–R4).docs/implementation-plan.md— 19 TDD tasks (write failing test → implement → pass → commit).
Key design decisions, all backed by real probing of pi -p output and external review:
cwd≠ session storage —spawn({ cwd })controls the working dir; Pi's session files use their default location (doesn't pollute the project).async default + handshake — new sessions wait for Pi's
sessionevent before returning (with asessionStartTimeoutMs), so the host always gets a realpiSessionId.Multi-stage scheduler —
plan()is reject → capacity → reuse → modify → mode, where modifiers stack rather than first-match (a lesson from review round 1).Progress redaction — tool results are truncated + scrubbed for tokens/keys before being stored.
Status
Working implementation, 140 passing tests. Not yet published to npm — run from source via tsx.
License
MIT
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables MCP clients to spawn and control Codex CLI and Claude Code sessions on the host machine, with session management and filesystem access.4MIT
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients like Claude Code to delegate coding tasks to the local Cursor Agent CLI, with persistent per-workspace sessions that resume across calls.12MIT
- AlicenseNot gradedqualityBmaintenanceDelegates bounded coding tasks from MCP clients to the Pi Coding Agent over stdio. Supports review, verification, implementation, and batch operations with long-running task polling.MIT
- AlicenseNot gradedqualityBmaintenanceEnables ChatGPT (or any MCP client) to delegate coding tasks to a local Hermes-backed agent with async job management, supporting read-only investigation, implementation, and continuation of sessions via secure MCP tunnel.1MIT
Related MCP Connectors
Persistent memory and cross-session learning for AI coding assistants (hosted remote MCP).
Personal assistant MCP server with search, execute, packages, jobs, secrets, and integrations.
A paid remote MCP for OpenAI Codex agent coordination MCP, built to return verdicts, receipts, usage
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/guyiicn/pi-subagent'
If you have feedback or need assistance with the MCP directory API, please join our Discord server