MCP Lab

Lab for developing custom MCP (Multi-Component Protocol) servers integrated with AI tooling. Enables modular AI workflows via VS Code-compatible servers. Designed for one-person developers building structured agent pipelines. Supports prompt design, sampling control, and tool orchestration. Includes example agents and tools for rapid iteration. Great for creating and debugging advanced agent infrastructure.

- MCP Lab
- Features
- Installation
- Quick Start
- Project Structure
- Example Servers
- Benefits
- How It Compares
- License

git clone https://github.com/harehimself/mcp-lab.git cd mcp-lab

cp .env.example .env # Edit .env with your API keys and settings

{ "mcpServers": { "mcp-lab": { "command": "python", "args": ["path/to/mcp-lab/src/servers/main_server.py"] } } }

- src/servers/: MCP server implementations
- src/tools/: Custom tool definitions
- src/agents/: Example agent configurations
- src/utils/: Utility functions and helpers
- tests/: Testing framework and examples
- examples/: Sample workflows and integrations

The lab includes several pre-built servers:

- File Operations: File system interaction and management
- Database Tools: Database query and manipulation tools
- API Integration: External API connection handlers
- Data Processing: Text and data transformation utilities
- Code Analysis: Code parsing and analysis tools

- Accelerates MCP server development with proven patterns
- Provides structured approach to agent pipeline creation
- Enables rapid prototyping and debugging of AI workflows
- Offers reusable components for common AI tasks
- Simplifies integration with existing development environments

- Purpose-built for solo developers creating agent infrastructure
- Focuses on modularity and rapid iteration over enterprise features
- Lightweight alternative to complex agent frameworks
- Seamless VS Code and Claude Desktop integration
- Emphasizes debugging and development experience

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