Skip to main content
Glama
yunuo110
by yunuo110

Engineering MCP

Engineering MCP is an AI engineering control plane built on the Model Context Protocol (MCP).

It coordinates trusted coding workers such as Codex-based workers and Generic Harness integrations while keeping repository ownership, task lifecycle, and execution authority under explicit control.

Unlike a model router, Engineering MCP does not decide which model should solve a problem or expose provider credentials to tasks. Instead, it provides the engineering coordination layer:

  • repository-bound task management;

  • controlled worker delegation;

  • lifecycle tracking and recovery;

  • worker result validation;

  • execution records;

  • trusted worker profile selection;

  • compatibility with multiple worker harnesses.

The system is designed around a simple principle:

Workers perform bounded execution. The control plane owns engineering state.

Engineering MCP keeps durable engineering truth in the repository, Git history, tests, and controlled ledger state rather than relying on temporary AI conversation context.

Installation

npm install -g engineering-mcp-cli

or:

npm install -g engineering-mcp-cli@beta

Related MCP server: lattice

Architecture

MCP Host / OWNER
       ↓
Engineering MCP
lifecycle · ledger · repo safety
       ↓
Trusted Worker Runner
       ↓
Native Harness Adapter
       ↓
Harness-managed Provider / Model

Harness-Native Execution Principle

Engineering MCP standardizes:

  • WHAT must be done (task contract)

  • lifecycle ownership

  • repository binding and Git verification

  • final Engineering Worker Protocol result contract

Native Harnesses decide:

  • HOW to reason

  • tool use

  • context management

  • model/provider selection

  • execution strategy

Engineering MCP is not a model router, universal model API, replacement Harness, or autonomous scheduler.

Quick start

npm install -g engineering-mcp-cli

engineering-mcp --help
engineering-mcp setup
engineering-mcp doctor
engineering-mcp profiles --worker-profiles /absolute/path/to/profiles.yaml

From inside a Git repository, start an OWNER server:

cd /path/to/repo
engineering-mcp --role owner

For local development from this repository:

npm ci
npm run typecheck
npm test
npm run build
node dist/cli.js --help

Verified capability matrix

Hosts

Host

Support

Grok CLI

VERIFIED

Codex CLI

VERIFIED FOR MCP STARTUP / AUTO-REPO

Grok CLI evidence includes real MCP OWNER use, cwd/subdirectory behavior, automatic repository binding, and real worker handoff. Codex CLI is verified for MCP startup and automatic repository discovery; do not treat broader Codex host scenarios as verified unless explicitly tested.

What it provides

Persistent task lifecycle and SQLite ledger Automated Worker Runner handoff Trusted Named Worker Profiles Codex CLI worker integration Generic CLI Harness Adapter Engineering Worker Protocol (engineering-worker/1) Automatic Git repository/worktree binding Git HEAD and scope verification Recovery and dispatch tracking Current-writer fencing across task, dispatch, and event state

Community / unverified

Harness

Label

Claude Code

COMMUNITY RECIPE — NOT MAINTAINER E2E VERIFIED

Qwen Code

COMMUNITY RECIPE — NOT MAINTAINER E2E VERIFIED

Kimi Code

COMMUNITY RECIPE — NOT MAINTAINER E2E VERIFIED

Other Harnesses

COMMUNITY RECIPE — NOT MAINTAINER E2E VERIFIED

Automatic repository binding

Default public story:

engineering-mcp --role owner

Resolution precedence:

1. --repo
2. ENGINEERING_MCP_REPO
3. launch cwd → git rev-parse --show-toplevel
4. fail closed

Properties:

  • a repo subdirectory resolves to the Git root;

  • a linked worktree resolves to its own worktree root;

  • outside Git fails with REPOSITORY_NOT_FOUND;

  • binding is immutable after process startup;

  • no ledger is opened on failed auto-discovery.

OWNER workflow

An OWNER process creates tasks, delegates to a Worker Harness, awaits the terminal result, and can recover or cancel a stuck task. The Worker Runner owns claim-time repository checks, process execution, result schema validation, and Git verification.

Core OWNER tools include:

  • create_task

  • get_task

  • list_active_tasks

  • list_worker_profiles

  • delegate_task

  • await_delegation

  • recover_task

  • resume_task

  • cancel_task

  • close_task

Worker Harnesses

Workers claim tasks through the trusted Worker Runner. Harnesses never own Engineering MCP lifecycle state. A Harness may be a native adapter (for example Codex CLI) or a declarative Generic CLI adapter.

Worker Profiles

Worker Profiles are trusted operator configuration that select a preconfigured Harness execution profile. They are loaded once at process startup and are immutable for the process lifetime.

OWNER
→ delegate_task(worker_profile = "my-generic-worker")
→ trusted Worker Profile registry
→ adapter + manifest + opaque Harness config
→ Worker Runner
→ native Harness

Use:

engineering-mcp --role owner --worker-profiles /absolute/path/to/profiles.yaml

OWNER can list trusted profiles with list_worker_profiles, and can select one with delegate_task(worker_profile = "...").

Without a profile file, the built-in codex-luna default preserves existing behavior. Worker Profiles do not allow task text to choose arbitrary models, providers, executables, or credentials. See Worker Profiles.

GenericCliAdapter

GenericCliAdapter executes a local Harness from a declarative engineering-cli-adapter/1 manifest. Manifests are shell-free: command, arguments, working directory, prompt transport, and result transport are explicit. Task text cannot select executables or argv.

Use:

engineering-mcp adapter validate manifest.yaml
engineering-mcp adapter probe manifest.yaml

adapter probe validates the manifest and then runs the equivalent of <command> --version with a bounded timeout and local execution only. It does not invoke a model or perform an authenticated smoke. adapter smoke, if exposed, is explicitly opt-in and may consume model quota.

Safety model

Engineering MCP is not an OS sandbox.

Trusted operator configuration can intentionally launch local Harness executables. External Harnesses run with the user's OS permissions. Engineering MCP control mechanisms include:

  • persistent task lifecycle;

  • one RUNNING slot;

  • execution-instance ownership;

  • writer-generation fencing;

  • repository binding;

  • HEAD verification;

  • allowed/forbidden scope verification;

  • explicit recovery;

  • fail-closed worker protocol.

Worker testimony is not Git authority. The Runner independently verifies Git state.

Recovery

Recovery is explicit and OWNER-only. If a Worker Runner disappears or a dispatch becomes orphaned, recover_task terminates the active dispatch atomically and returns the task to a delegable state. cancel_task performs a similar termination for cancellation.

Support tiers

  • VERIFIED — maintainer real authenticated E2E.

  • VERIFIED CORE — core mechanism has real E2E evidence, but not every third-party Harness.

  • COMMUNITY — recipe/config exists but maintainer has no authenticated E2E.

  • EXPERIMENTAL — evidence exists but upstream interface is unstable/developer-preview.

  • PLANNED — not implemented or not validated.

Limitations

  • one RUNNING task slot;

  • no autonomous scheduler;

  • no parallel RUNNING;

  • no auto commit/merge;

  • no remote runners or cloud service;

  • no provider router;

  • no web UI;

  • no heartbeat/lease subsystem yet.

Validation

Release validated with:

  • TypeScript build

  • complete automated test suite

  • Linux / Windows / macOS CI

  • npm packed artifact installation test

Contribution / docs

See:

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

No tool schema history has been recorded yet.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    A
    maintenance
    Provides bounded repository context and edit-grant MCP tools to coding agents such as Codex, indexing local repositories and enabling fingerprint-checked patch application.
    15
    Apache 2.0
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI coding agents and hosts to enforce deterministic repository boundaries via MCP, providing structured reads, supervised edits, snapshots, audits, and recovery with machine-readable evidence.
    MIT

Latest Blog Posts

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/yunuo110/engineering-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server