pi-subagent
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: Claude Code Manager WAN
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 |
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.
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 (79 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, 79 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
- Alicense-qualityCmaintenanceEnables MCP clients to spawn and control Codex CLI and Claude Code sessions on the host machine, with session management and filesystem access.4MIT
- Flicense-qualityCmaintenanceEnables ISLI agents and MCP clients to dispatch natural-language coding and terminal tasks to a locally-installed Claude Code CLI, supporting both one-shot execution and persistent sessions with workspace and security controls.
- Alicense-qualityBmaintenanceEnables 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
- Flicense-qualityCmaintenanceExposes Sylvan's MCP tools to a Pi coding agent, enabling management of spaces and developer shells.
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