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Opafex

Intelagent MCP Template

by Opafex
README.md
# My MCP Server

A [Model Context Protocol](https://modelcontextprotocol.io/) server built with [@opafex/mcp-shared](https://github.com/opafex/Opafex-MCPs).

## Quick Start

```bash
npm install
npm run build
npm start
```

## Add to Claude Code

Create `.mcp.json` in your project root:

```json
{
  "mcpServers": {
    "my-mcp-server": {
      "command": "node",
      "args": ["path/to/dist/index.js"]
    }
  }
}
```

## Tools

| Tool | Description |
|------|-------------|
| `reverse_string` | Reverse a string |
| `word_count` | Count words and characters |
| `server_info` | Server metadata and health check |

## Development

```bash
npm run dev       # Run with tsx (no build needed)
npm run build     # Compile TypeScript
npm test          # Run tests
npm run test:watch # Watch mode
```

## Adding a New Tool

1. Define types in `src/types.ts`
2. Add business logic to a service in `src/services/`
3. Define the tool in `src/tools/` using the `ToolDefinition` interface
4. Wire it up in `src/index.ts`
5. Add tests in `tests/`

See the [enrichment MCP](https://github.com/opafex/Opafex-MCPs/tree/main/packages/enrichment) for a full production example.

## License

MIT

TDQS

A3.9/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: reverse_string manipulates string order, word_count analyzes string content, and server_info provides metadata. There is no overlap in functionality, making tool selection unambiguous.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with clear verb_noun structure (reverse_string, server_info, word_count). The naming is predictable and readable throughout the set.

Tool Count3/5

With only 3 tools, the set feels thin for a general-purpose 'Intelagent MCP Template' server, suggesting limited scope or utility. However, the count is not extreme and could be appropriate for a minimal template.

Completeness3/5

For a template server, the tools cover basic string operations and introspection, but there are notable gaps in common utility functions (e.g., text formatting, mathematical operations). The surface is functional but incomplete for broader agent tasks.

Maintenance

ActivityStale
ResponsivenessNo issues