mcp_input_analyzer

What is mcp_input_analyzer?

mcp_input_analyzer is an open-source Python library that analyzes user‑described build features (databases, API integrations, tools) and extracts core server requirements—such as resources, tools, prompts, external systems, and transports—for MCP (Microservices Configuration Platform). It converts free‑form text descriptions into structured, MCP‑compliant input definitions.

How to use mcp_input_analyzer?

Install via pip: pip install mcp-input-analyzer (requires Python 3.6+). Import the MCPAnalyzer class, initialize it with a description string and optional fallback_behavior parameter, then call methods like extract_requirements(), generate_mcp_structure(), or create_claude_json() to obtain the desired output.

Key features of mcp_input_analyzer

• Natural language to structured build feature extraction
• MCP‑compliant input structure generation
• Validation of supported tools and protocols
• Claude‑readable JSON definition creation
• Fallback logic for unsupported build features

Use cases of mcp_input_analyzer

• Automatically generating MCP server configurations from feature descriptions
• Translating team requirements into structured dependency definitions
• Creating Claude‑compatible JSON inputs for downstream processing
• Validating whether specified tools and protocols are supported

FAQ from mcp_input_analyzer

What Python version is required?

Python 3.6 or higher is required.

How do I install mcp_input_analyzer?

Install via pip: pip install mcp-input-analyzer. Alternatively, clone the repository and run pip install . from the source directory.

What does the library output?

It can output a dictionary of structured server requirements (extract_requirements()), an MCP‑compliant input structure (generate_mcp_structure()), or a Claude‑readable JSON definition (create_claude_json()).

Does mcp_input_analyzer handle unsupported features?

Yes, it includes fallback logic. The MCPAnalyzer constructor accepts a fallback_behavior parameter (default or custom) to control how unsupported features are handled.

Is mcp_input_analyzer production‑ready?

No. The library is currently in early development and some tests may be failing. Contributions to fix issues are welcome.