Docker Pibox MCP Server

docker-pibox

pi-coding-agent inside an aicodebox container. One image, several ways in: interactive shell, one-shot prompt, HTTP API (with an OpenAI-compatible endpoint), MCP server, Telegram bot, and a cron scheduler that fires pi on whatever schedule you want.

You talk to pibox. pibox talks to pi. pi talks to whatever LLM you point it at. Nobody cares about the middle.

Table of Contents

• Quick start
• Modes
  • API mode
  • Telegram mode
  • Cron mode
  • MCP mode
• Configuration
• Auth
• Agent integrations
• Development
• Tests
• License

Quick start

# one-shot prompt
docker run --rm \
  -e ANTHROPIC_AUTH_TOKEN=your-token \
  -e ANTHROPIC_BASE_URL=https://api.z.ai/api/anthropic \
  -e ANTHROPIC_MODEL=glm-4.6 \
  psyb0t/pibox:latest \
  -p "list the files in /workspace"

# API server
docker run -d --network host \
  -e PIBOX_API_MODE=1 \
  -e PIBOX_API_MODE_TOKEN=your-secret \
  -e PIBOX_AVAILABLE_MODELS=glm-4.6,glm-4.5-air \
  -e ANTHROPIC_AUTH_TOKEN=your-token \
  -e ANTHROPIC_BASE_URL=https://api.z.ai/api/anthropic \
  -e ANTHROPIC_MODEL=glm-4.6 \
  -v "$PWD/workspace:/workspace" \
  psyb0t/pibox:latest

Modes

Foreground modes (API / Telegram / Cron) are mutually exclusive — except PIBOX_TELEGRAM_MODE=1 + PIBOX_CRON_MODE=1, which run together (cron in-thread inside telegram). API wins if set alongside anything else.

MCP mode (PIBOX_MCP_MODE=1) is independent — it coexists with whatever foreground mode is running. In API mode it's mounted at /mcp on the API port; in other modes it runs as a sidecar uvicorn on its own port.

Each mode has its own page with full setup, env vars, and examples.

API Mode →

Long-lived FastAPI server on :8080. Agent runs (sync, async with run-id polling, cancellable), workspace file upload/download/list/delete with traversal checking, and an OpenAI-compatible chat/completions endpoint with streaming and client-executed tool calling.

environment:
  - PIBOX_API_MODE=1
  - PIBOX_API_MODE_TOKEN=your-secret
  - PIBOX_AVAILABLE_MODELS=glm-4.6,glm-4.5-air

Telegram Mode →

Talk to pi from Telegram. Per-chat isolated workspaces, allowed-chats and per-chat allowed-users gating, file ingestion, [SEND_FILE: path] to get files back, and per-chat /model, /effort, /system_prompt, /append_system_prompt overrides that persist across restarts.

environment:
  - PIBOX_TELEGRAM_MODE=1
  - PIBOX_TELEGRAM_MODE_TOKEN=123456:ABC

Cron Mode →

YAML-defined scheduled jobs on 6-field croniter schedules. Per-run history dirs with meta.json, stdout.log, stderr.log, result.txt, and a "prior run" hint so a job can reference its own history.

environment:
  - PIBOX_CRON_MODE=1
  - PIBOX_CRON_MODE_FILE=/home/aicode/.aicodebox/cron.yaml

MCP Mode →

Exposes run_prompt plus workspace-confined file tools over streamable HTTP, so other agents can drive pi as a tool. Coexists with any foreground mode — mounted at /mcp on the API port in API mode, a sidecar on its own port everywhere else.

environment:
  - PIBOX_MCP_MODE=1
  - PIBOX_MCP_MODE_TOKEN=your-secret

Configuration

Naming convention: PIBOX_<MODE>_MODE=1 is the on/off flag, PIBOX_<MODE>_MODE_<KNOB>=... is its config. Non-mode-scoped vars (workspace, container name, available models) are bare.

The image is built on top of aicodebox, so the equivalent AICODEBOX_* names also work — the entrypoint translates PIBOX_X to AICODEBOX_X when only the pibox-prefixed one is set. If you set both, AICODEBOX_* wins.

Mode flags

Each mode's own knobs (ports, tokens, config paths, history dirs) live on that mode's page: api.md, telegram.md, cron.md, mcp.md.

Workspace & runtime

Auth

pi speaks the Anthropic wire protocol. Point it at any Anthropic-compatible endpoint:

Z.AI's GLM models are fast and cheap for most tasks — ANTHROPIC_BASE_URL=https://api.z.ai/api/anthropic + ANTHROPIC_MODEL=glm-4.6 is the recommended default.

pi's thinking levels (--thinking): off, minimal, low, medium, high, xhigh. Exposed as the /effort command in telegram mode and as thinking in API requests.

Agent integrations

The skill works in any agent that reads .agents/skills/, and installs natively in the clients below.

Claude Code

claude plugin marketplace add psyb0t/agents
claude plugin install pibox@psyb0t

Claude Code prompts for the pibox URL and, if auth is enabled, the API and MCP tokens — sensitive values are stored in your OS keychain.

Codex

codex plugin marketplace add psyb0t/agents
codex plugin add pibox@psyb0t

Installed via the marketplace, the skill invokes as $pibox:pibox. Codex also picks the skill up automatically with no install in any repo containing .agents/skills/, where it invokes as plain $pibox.

OpenClaw

The skill is published to ClawHub on every release:

openclaw skills install @psyb0t/pibox

For MCP clients that speak local stdio, the @psyb0t/pibox plugin bridges to the service's /mcp endpoint:

openclaw plugins install clawhub:@psyb0t/pibox

Then set PIBOX_URL (and PIBOX_MCP_MODE_TOKEN if the server was started with MCP auth enabled).

Development

make help   # list targets
make build  # pull the published aicodebox base, build + tag psyb0t/pibox:v<VERSION> and :latest
make test   # run the full e2e suite (needs .env.test)
make clean  # remove built images

VERSION is read from pibox/pyproject.toml. make build pulls the published psyb0t/aicodebox base pinned in the Dockerfile; set SKIP_BASE_PULL=1 to use a locally-built base instead (e.g. from a sibling ../docker-aicodebox checkout), or override with make build BASE_IMAGE=....

Tests

End-to-end tests build the image and run it against a real LLM endpoint. Telegram tests use psyb0t/telethon-plus as a real MTProto userbot.

cp .env.test.example .env.test
$EDITOR .env.test   # fill in ANTHROPIC_* and optionally Telegram creds
make test

Telegram tests auto-skip if AICODEBOX_TELEGRAM_MODE_TOKEN is empty. Everything else only needs ANTHROPIC_AUTH_TOKEN + ANTHROPIC_BASE_URL.

License

WTFPL — see LICENSE. Do what the fuck you want.