AgentTasker for Pi & OMP

Plan work. Run four shell jobs at once. Collect the results.

A dependency-free stdio MCP server for Pi and OMP. Your existing model makes the plan; AgentTasker runs the commands. No extra model account, API key or hosted service.

• Configurable concurrency, background batch IDs and dependency ordering.

• Per-command exit codes, stdout/stderr tails, host, cwd and timing.

• Timeouts and cancellation of running shell process groups.

• Explicit local or SSH execution; no silent local fallback.

• Profile-aware installer that preserves other MCP entries and makes private backups.

Requires: Python 3.10+, Git and Bash on Linux/macOS/WSL. First installation needs pip/build-tool downloads. SSH mode needs OpenSSH and an already-authorized POSIX host. Native Windows shell execution is not supported.

--allow-shell permits arbitrary commands as the server user. This is not a sandbox. Commands run on the MCP server's host, not automatically on your agent's SSH host. Security and boundaries.

Copy this to your agent

Install https://github.com/S3bRR/AgentTasker-for-Pi-OMP from a fresh clone in a
stable location. Read README.md, SECURITY.md and the installer before running it.
Confirm my client (Pi/OMP), active profile's exact mcp.json, execution host
(local or an explicitly authorized SSH host), and existing workspace directory.
Ask for missing choices; never guess a VM or copy another profile's route.

Use install.py with four workers and --allow-shell only on my chosen host.
Preview the generated entry, then merge with --apply. Preserve other servers,
models, credentials and safety policies. Ask before replacing a different
agent-tasker entry with --replace. Never print secrets or bypass host-key checks.

Run the doctor --shell-test, then verify in a fresh/reloaded agent session:
execute_batch(wait=false, concurrency=4), collect with get_batch, and check
outputs, exits, host/cwd and overlap. A client-only check does not verify a
custom tool guard. If blocked, report it; do not disable policies or fall back
locally. Report config changes, backups, checks and anything unverified.

Related MCP server: par5-mcp

Install locally

Clone to a stable location. Replace the workspace placeholder with an existing directory on the machine where commands should run:

git clone --depth 1 https://github.com/S3bRR/AgentTasker-for-Pi-OMP.git
cd AgentTasker-for-Pi-OMP
./setup.sh --client pi --cwd /absolute/workspace --allow-shell --apply

• Pi: respects PI_CODING_AGENT_DIR, otherwise uses ~/.pi/agent/mcp.json. Pass --config /absolute/active/mcp.json for a custom profile.

• OMP: replace --client pi with --client omp --config /absolute/active/mcp.json, or --client omp --profile YOUR_NAMED_PROFILE. Its standard default config is ~/.omp/agent/mcp.json; the active profile is never guessed.

• Preview: omit --apply to install and print config without changing client settings.

• Options: python3 install.py --help. Default workers: 4; configurable 1–256. --skip-install generates/merges config using an existing --venv.

The installer creates .venv in the checkout. Keep both in place. It rejects malformed/duplicate-key JSON, symlink config targets and unapproved collisions. --replace --apply changes only an existing AgentTasker entry after review. Backups are private mcp.json.backup-* files beside your config; never share them. No models, approval policies or agent instructions are changed.

Run on a VM instead

Do not use the local entry for a remote-only profile.

1. On the authorized VM, clone this repo and run python3 install.py --client generic --cwd /absolute/remote/workspace --allow-shell. This installs there and prints the remote venv's absolute Python path.

2. On the client, generate the SSH entry using that path:

python3 install.py --client pi --transport ssh \
  --ssh-host YOUR_AUTHORIZED_SSH_ALIAS \
  --remote-python /absolute/remote/AgentTasker-for-Pi-OMP/.venv/bin/python \
  --cwd /absolute/remote/workspace --allow-shell --apply

Use the same OMP/profile options described above. Optional: --ssh-config PATH for an existing client SSH config, or --ssh-port PORT. SSH mode does not create a local execution server or connect automatically. Authenticate and verify the host key through your normal workflow first. No credentials are copied.

Verify and use

Reload/restart the selected client. From the checkout:

python3 -m agent_tasker_mcp.doctor --config /absolute/active/mcp.json --shell-test

Or use .venv/bin/agent-tasker-doctor after local installation. The doctor checks four-way overlap, outputs/exits, failed-dependency isolation, cancellation and timeouts using harmless commands on the configured host. Check its reported host and cwd. Omit --shell-test for protocol-only verification.

Then ask the model to run four harmless jobs through AgentTasker and collect them. A custom VM-only guard may still block model calls even if the doctor passes. Obtain approval for the exact trusted MCP source and SSH transport—never a namespace wildcard. Do not disable the guard. Headless OMP tests with explicit --tools may need process-only OMP_MCP_STARTUP_TIMEOUT_MS=5000 on cold startup.

Example execute_batch arguments:

{
  "wait": false,
  "concurrency": 4,
  "tasks": [
    {"name": "identity", "task_type": "shell", "command": "id", "timeout": 10},
    {"name": "directory", "task_type": "shell", "command": "pwd", "timeout": 10},
    {"name": "files", "task_type": "shell", "command": "ls -la | head -20", "timeout": 10},
    {"name": "platform", "task_type": "shell", "command": "uname -s", "timeout": 10}
  ]
}

Collect with {"batch_id":"RETURNED_ID","wait_seconds":5,"output_mode":"full"}. Use depends_on:["earlier-name"] only for ordering. Optional task fields: absolute execution-host cwd, string env overrides, timeout (default 30 seconds), and max_output_bytes (retained tail per stream: default 8192, maximum 65536). Compact output shows finished tasks; full output includes queued/running placeholders. Check every status, exit code and truncation flag. A failure blocks dependants, not unrelated jobs. cd and environment changes do not persist across tasks.

For your active profile's AGENTS.md, a short optional note is enough:

Use AgentTasker for independent shell work: plan first, execute_batch with wait:false and concurrency:4, then get_batch. Check outputs, exits and host/cwd. Use depends_on for ordering and cancel_batch to stop work. Avoid concurrent writes to the same worktree. Never retry side effects blindly after disconnect.

Limits and maintenance

• Jobs/results are session-local and disappear on MCP/client restart or SSH loss.

• No live stdout streaming or durable log storage. Redirect to a host file for full logs.

• Four workers per server process, not per entire machine. Separate clients have separate limits.

• No automatic shell retries. Process-group cleanup cannot contain deliberately detached processes or guarantee cleanup after SIGKILL, transport loss or host failure.

• Resource defaults: 1000 tasks/batch, 1 MB payload/task, 32 retained batches, 1-hour completed retention. Override with AGENT_TASKER_MAX_TASKS, AGENT_TASKER_MAX_PAYLOAD_BYTES, AGENT_TASKER_MAX_BATCHES, AGENT_TASKER_BATCH_TTL_SECONDS on the server.

• 2.0 is shell-only: optional web/search/downstream-MCP tasks and their CLI flags from 1.x were removed. Existing shell task/config arguments are unchanged.

Update after collecting active work: git pull --ff-only, then .venv/bin/python -m pip install .. Reload the client and rerun verification. To uninstall, remove only agent-tasker from the selected config, reload, then remove unused installations. Do not restore an old whole-config backup over unrelated newer settings.

CI verifies source/wheel installs and the doctor on Linux/macOS with Python 3.10/3.12. Build with .venv/bin/python -m pip install build && .venv/bin/python -m build. No test suite or extra runtime dependencies are shipped. MIT license; original attribution is preserved.