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coding-agent-mcp

Local, client-agnostic MCP server for supervising and orchestrating coding agents such as Muse and AGY.

The MCP server is the safe execution, isolation, and verification boundary. OpenAI/ChatGPT, Claude Desktop, custom MCP orchestrators, or any other compatible client act as external supervisors.


Features

  • Safe Local Execution: Interacts with local agents without exposing arbitrary shell execution.

  • Git Worktree Isolation: Spawns tasks in isolated Git worktrees by default, protecting current work and enabling safe concurrency.

  • Client-Agnostic MCP Surface: Standard MCP tools compatible with any client:

    • list_agents

    • list_repositories

    • start_task

    • continue_task

    • get_task

    • get_task_output

    • cancel_task

    • get_repo_status

    • get_diff

    • run_verification

  • Deterministic Verification: Independent test and lint execution profiles returning real exit codes and outputs.

  • Agent Adapters: Pluggable adapters for Muse and AGY with headless execution, permission management, and session resumption. The optional agy-gemini adapter runs the installed AGY CLI through agy-gyro with an isolated Gemini API-key profile, avoiding account OAuth and Keychain.

  • Durable Persistence & Audit: SQLite-backed task state, streaming logs, and structured audit logs with crash recovery.


Related MCP server: Vibechemy

Quick Start

1. Install & Build

npm install
npm run build

2. Configuration

Create ~/.coding-agent-mcp/config.yaml (or copy examples/config.example.yaml):

server:
  data_dir: ~/.coding-agent-mcp
  max_concurrent_tasks: 2

repositories:
  my-repo:
    root: /path/to/my-repo
    writable: true
    default_workspace_strategy: worktree
    verification_profiles:
      test:
        command: ["npm", "test"]
        timeout_seconds: 900
      lint:
        command: ["npm", "run", "lint"]
        timeout_seconds: 300

3. Run Server

node dist/index.js --config /path/to/config.yaml

Running Tests

npm test

Runs the test suite covering unit policies, Git worktree isolation, task lifecycle, and end-to-end MCP tool invocations.


Documentation


License

MIT

Available Tools

10 tools
cancel_taskA

Cancels a running coding-agent task

Inputs: task_id (required).

continue_taskA

Sends follow-up instructions to an existing task session

Inputs: task_id (required), instruction (required).

get_diffA

Returns the Git diff for a task workspace or configured repository (including committed changes since task base SHA and untracked files)

Inputs: staged, task_id, max_bytes, repository.

get_repo_statusA

Returns structured Git status for a task workspace or configured repository

Inputs: task_id, repository.

get_taskB

Returns task state and concise metadata

Inputs: task_id (required).

get_task_outputA

Returns bounded task output with pagination cursor support

Inputs: task_id (required), cursor, max_bytes.

list_agentsA

Returns configured coding agents and their local availability

Inputs: no named parameters.

list_repositoriesA

Returns configured repository aliases and safe metadata

Inputs: no named parameters.

run_verificationB

Runs a configured verification profile (e.g. test, lint) in a task workspace or repository

Inputs: profile (required), task_id, repository.

start_taskB

Starts a coding-agent task in a configured repository workspace

Inputs: agent (required), repository (required), instruction (required), mode, +1 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

    TDQS

    A3.8/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool addresses a distinct resource or action: agent discovery, repository discovery, task lifecycle management, output retrieval, git inspection, and verification. There is no meaningful overlap between get_task and get_task_output, or between get_repo_status and get_diff.

    Naming Consistency5/5

    All tools follow a consistent snake_case verb_noun pattern (list_*, start_*, cancel_*, continue_*, get_*, run_*). The naming is predictable and makes the action-resource relationship clear across the entire set.

    Tool Count5/5

    Ten tools is well-scoped for a coding-agent orchestration server. Each tool covers a necessary operation without redundancy, and the count is within the ideal range for maintainability and agent usability.

    Completeness5/5

    The tool surface covers the full task lifecycle: create (start_task), read (get_task, get_task_output), update (continue_task), and cancel (cancel_task). It also provides discovery (list_agents, list_repositories), repository inspection (get_repo_status, get_diff), and verification (run_verification), leaving no obvious dead ends for the stated purpose.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing

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