MCP Server Overview

APiGen includes a Model Context Protocol (MCP) server that enables AI assistants to generate API code conversationally.

What is MCP?

MCP (Model Context Protocol) is a standard protocol developed by Anthropic for connecting AI assistants to external tools and data sources. It allows AI models like Claude to:

• Call tools (functions) with specific parameters
• Access resources (data) from external systems
• Maintain context across conversations

Why MCP for Code Generation?

Traditional code generation requires:

1. Writing SQL schemas manually
2. Running CLI commands with correct flags
3. Understanding all available options

With MCP, you can simply describe what you need:

"Generate a REST API for a blog system with users, posts, and comments using Python FastAPI"

The AI assistant understands the request and calls the appropriate APiGen tools.

Available Implementations

Java MCP Server

Native integration with the codegen engine.

• Direct access to all generators
• No subprocess overhead
• Full type safety

# Build and run
./gradlew :mcp:java:build
java -jar mcp/java/build/libs/java-1.0.0-SNAPSHOT-all.jar

Learn more →

Python MCP Server

Lightweight wrapper using CLI subprocess.

• Easy to install (pip install)
• Quick setup
• Uses existing CLI

# Install and run
cd mcp/python
pip install -e .
apigen-mcp

Learn more →

Tools Available

Both implementations provide the same tools:

Tool	Description
generate_from_sql	Generate complete API from SQL schema
preview_sql	Preview generated code without writing files
parse_sql	Parse SQL and return table structure
list_languages	List supported programming languages
list_databases	List supported database types

Resources Available

Static resources for reference:

Resource URI	Description
apigen://languages	Supported languages with descriptions
apigen://databases	Supported database types
apigen://field-types	Available field types
apigen://example/sql	Example SQL schema

Configuration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "apigen": {
      "command": "java",
      "args": ["-jar", "/path/to/apigen/mcp/java/build/libs/java-1.0.0-SNAPSHOT-all.jar"]
    }
  }
}

Other MCP Clients

Any MCP-compatible client can connect using:

• Transport: stdio (standard input/output)
• Protocol: JSON-RPC 2.0
• Version: 2024-11-05

Example Conversation

User: Create a REST API for a task management system with users, projects, and tasks. Use TypeScript with NestJS.

AI Assistant (using APiGen MCP):

I'll generate that for you. Let me first parse the schema and then generate the code.

[Calls parse_sql tool]

Found 3 tables:
- users (4 columns)
- projects (5 columns)
- tasks (7 columns)

[Calls generate_from_sql tool with language=typescript-nestjs]

Generated 24 files:
- src/users/users.entity.ts
- src/users/users.dto.ts
- src/users/users.controller.ts
- src/users/users.service.ts
- src/projects/...
- src/tasks/...
- prisma/schema.prisma
- package.json
- tsconfig.json

Comparison

Feature	Java MCP	Python MCP
Integration	Native	Subprocess
Startup Time	Slower (JVM)	Faster
Performance	Better	Good
Dependencies	Java 25+	Python 3.10+, Java CLI
Best For	Production	Quick setup

Next Steps

• Java MCP Setup - Native server configuration
• Python MCP Setup - Python wrapper configuration
• Tools Reference - Detailed tool documentation