codeops-mcp

MCP (Model Context Protocol) server providing AI coding agents with universal, language-agnostic development rules.

What It Does

codeops-mcp bundles 7 curated rule documents that teach AI agents how to code, test, plan, commit, and behave — across any programming language and project type. It exposes these rules via 5 MCP tools.

Rule Documents

| Rule | Description | |------|-------------| | code | 30 coding standards: DRY, testing, documentation, architecture, type safety | | testing | Test commands, workflows, coverage requirements, debugging strategies | | git-commands | Git commit protocols (gitcm/gitcmp), message format, push workflow | | make_plan | Complete protocol for creating and executing multi-document implementation plans | | plans | 10 rules for structuring plans: phases, tasks, dependencies, architecture | | agents | Mandatory AI agent behavior: compliance, context management, multi-session execution | | project-template | Template for .clinerules/project.md — project-specific toolchain configuration |

MCP Tools

| Tool | Description | |------|-------------| | get_rule | Get any rule document by name (supports aliases like "git", "test") | | list_rules | List all available rules grouped by category | | search_rules | Full-text search across all rules with TF-IDF ranking | | analyze_project | Killer feature — Scan a project directory and auto-generate project.md | | get_setup_guide | Step-by-step guide for setting up CodeOps in a project |

Installation

# Global install
npm install -g codeops-mcp

# Or with yarn
yarn global add codeops-mcp

MCP Configuration

Add to your MCP client configuration (e.g., Cline, Claude Desktop):

{
  "mcpServers": {
    "codeops": {
      "command": "codeops-mcp"
    }
  }
}

Custom docs path

{
  "mcpServers": {
    "codeops": {
      "command": "codeops-mcp",
      "args": ["/path/to/custom/docs"]
    }
  }
}

Or via environment variable:

{
  "mcpServers": {
    "codeops": {
      "command": "codeops-mcp",
      "env": {
        "CODEOPS_DOCS_PATH": "/path/to/custom/docs"
      }
    }
  }
}

How It Works

The two-layer architecture:

1. Layer 1: Universal rules (bundled in this package) — Language-agnostic standards
2. Layer 2: Project-specific config (.clinerules/project.md in your project) — Toolchain, commands, conventions

All generic rules reference project.md for project-specific settings like build commands, test commands, package manager, etc.

Quick Setup

1. Run analyze_project("/path/to/your/project") to auto-detect your toolchain
2. Save the output to .clinerules/project.md in your project
3. The AI agent automatically applies universal rules using your project's settings

Development

# Install dependencies
yarn install

# Build
yarn build

# Run tests
yarn test

# Watch mode
yarn test:watch

Architecture

src/
├── index.ts              # MCP server entry point
├── config.ts             # Configuration resolution
├── types/
│   └── index.ts          # Type definitions & constants
├── store/
│   ├── rule-store.ts     # In-memory document store
│   └── search-engine.ts  # TF-IDF search engine
├── tools/
│   ├── get-rule.ts       # Get rule by name
│   ├── list-rules.ts     # List all rules
│   ├── search-rules.ts   # Full-text search
│   ├── analyze-project.ts # Project analysis & project.md generation
│   └── get-setup-guide.ts # Setup instructions
└── __tests__/
    ├── store/            # Store & search engine tests
    └── tools/            # Tool integration tests
docs/                     # Bundled rule markdown files

License

MIT