omp-worker-mcp

MCP serverProductivity

Lets your agent hand complete coding tasks to a local OMP model and check the results.

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About this server

Delegate complete coding tasks to the local OMP default model and inspect the result.

Getting started

  1. Save this item in Your setup as a reference.
  2. Read the source or reference documentation for its setup requirements. Saving it here does not connect it to your AI.
  3. Check this page for availability before trying to install it through ahel.

From the project's README

As published by divenire990/omp-worker-mcp in README.md.

Durable Model Context Protocol (MCP) server for delegating background coding tasks and DAG workflows to local Oh My Pi (OMP) CLI sub-agents.

Quick Start • Entrypoints • Safety Contract • Platform Support • Docs Hub


Value & Operating Model

omp-worker-mcp implements an outcome-led Supervisor-Worker pattern that decouples high-level planning from concrete implementation:

  • Main Agent Remains in Control: The primary host harness (e.g., Codex, Claude Code) retains full authority over architecture, task decomposition, trade-off decisions, and final acceptance review.
  • Durable Local Background Execution: Concrete, long-running coding, refactoring, and exploratory tasks are offloaded to local OMP worker processes running in the background without blocking conversational turns.
  • Topological DAG Orchestration: Independent work units can be orchestrated as a directed acyclic graph (DAG) with automated dependency resolution, concurrency limits, and failure containment.
  • Explicit Path Ownership Boundaries: Write tasks must declare explicit write-path ownership. The server validates and rejects overlapping concurrent write scopes in batch DAGs, supplying declared boundaries as worker constraints to prevent write collisions.
  • Structured Results & Supervised Resumption: Workers report deliverables via the structured OMP_WORKER_RESULT envelope (status, summary, artifacts, verification checks, remaining items). Supervisors can inspect logs in real time and inject corrective guidance via omp_continue to retry within the same session.

Installation & Quick Start

1. Install OMP

Install Oh My Pi (OMP) from its official project. (Note: running omp-worker-mcp requires local Node.js >= 22.0.0.)

2. Verify OMP Reachability

Verify that the OMP CLI is reachable in your environment:

omp --version

Troubleshooting: If omp is not on your PATH, set OMP_WORKER_OMP_COMMAND to its executable path in your MCP configuration.

3. Configure OMP & Default Worker Model

Run omp setup in your terminal to authenticate, configure your local OMP environment, and select your default worker model. This default model is what background OMP workers use during task execution.

(Optional advanced configuration): You can specify your default model via modelRoles.default: <provider>/<model> in ~/.omp/agent/config.yml. For upstream configuration options, see Oh My Pi.

4. Install / Register omp-worker-mcp from npm via npx & Restart Host

Add omp-worker-mcp to your host harness's stdio mcpServers configuration. The host runs the published npm package using npx -y omp-worker-mcp, which downloads and caches it on first use; ordinary users do not need git clone or npm install -g. Keep the JSON configuration below as the executable setup and restart your host harness:

{
  "mcpServers": {
    "omp-worker": {
      "command": "npx",
      "args": ["-y", "omp-worker-mcp"],
      "env": {
        "OMP_WORKER_OMP_COMMAND": "omp"
      }
    }
  }
}

For detailed client configurations covering Codex (config.toml), Claude Code, Cursor, VS Code / GitHub Copilot, Windsurf Cascade, and Continue, see Client Configurations.

5. Send Your First Prompt

After restarting your host harness, paste a read-only inspection prompt directly into your conversation to verify the full delegation chain:

Please use the configured omp-worker-mcp to perform a read-only inspection of the current workspace, review the project structure and dependencies, and provide a concise summary report. Do not modify any files.

For Contributors / Local Development: Building from Source

git clone https://github.com/divenire990/omp-worker-mcp.git
cd omp-worker-mcp
npm ci
npm run build
npm test

Recommended Entrypoints

While MCP registration and policy heuristics guide host harnesses to select high-level entrypoints based on task complexity, automatic invocation is not guaranteed. Users may also explicitly request omp-worker-mcp in prompts when delegation is critical or if the host falls back to direct execution:

  • omp_run_compact (Single Task): High-level single-task entrypoint selected by the host to delegate a discrete coding or research assignment, wait up to wait_seconds for execution, and return a compact structured summary and artifact list.
  • omp_run_batch_compact (Multi-Task / DAG): High-level multi-task entrypoint selected by the host to dispatch interdependent tasks with explicit dependency graphs and concurrency limits, waiting for aggregated results.

For lower-level primitives (omp_delegate, omp_wait, omp_result, omp_continue, omp_cancel, omp_wait_group, omp_cancel_group) and complete schemas, consult the Tool Reference.


Task Safety & Ownership

  1. Declared Write Ownership in Batch DAGs: In batch DAG tasks (omp_run_batch_compact), write task items must explicitly declare the workspace paths they own via ownership, while read_only task items declare no write scope. For single-task execution (omp_run_compact), read-only and no-modification constraints are expressed directly in goal and acceptance.
  2. DAG Overlap Validation: The server validates batch groups and rejects concurrent tasks with overlapping write scopes; tasks operating on shared paths must declare sequential depends_on dependencies.
  3. Structured Verification Contract: Subagents deliver results using the structured OMP_WORKER_RESULT envelope (status, summary, artifacts, verification checks, remaining items).

High-impact operations (e.g., npm publish, git push, production deployments, secret modification) must always remain under direct host harness and human supervision.


Platform Support & Boundaries

  • Upstream Engine: Interfaces with the Oh My Pi (OMP) CLI (MIT License). The upstream binary is not bundled and must be installed separately in your local runtime PATH.
  • Runtime Requirement: Node.js >= 22.0.0 (native ECMAScript Modules and modern Node.js APIs).
  • Operating Systems:
    • Windows and macOS (Apple Silicon): Verified with Node.js 22+ and real OMP CLI end-to-end testing.
    • Linux: Supported by the architecture, but awaiting broader production verification.
  • Support Tiers:
    • Author-Verified: Codex (author's daily local workflow; not a cross-platform CI guarantee).
    • Documented / Reproducible: Claude Code, Cursor, VS Code / GitHub Copilot, Windsurf Cascade, Continue (not CI integration-tested).
    • Cloud / Remote Hosts: Conditional (requires complete runtime, OMP CLI in PATH, writable workspace, and process spawning permissions).

Documentation Hub

Detailed documentation is organized in the docs/ directory:


Compatibility & Changelog

  • Public Contract & Deprecation: Review COMPATIBILITY.md for versioning guarantees.
  • Release History: Review CHANGELOG.md for notable updates.

License

This project is licensed under the MIT License.

Signals

GitHub stars
2
Last commit
Aug 2026
Weekly downloads
55
Weekly_downloads
45 weekly_downloads
Advanced
Delivery
omp-worker-mcp MCP server → your ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
io-github-divenire990-omp-worker-mcp
Source
github.com/divenire990/omp-worker-mcp