MCP Input Analyzer

@Sumedh1599

リポジトリ

基本情報

カテゴリ

開発者ツール

トランスポート

stdio

作者

Sumedh1599

MCP Input Analyzer について

Analyzes user-described build features (e.g. database, API integration, tools) and extracts core server requirements like resources, tools, prompts, external systems, and transports needed for MCP.

#open-source #machine-learning #library #ai#natural-language-to#mcp-compliant-input#validation-of-suppor#claude-readable-json#fallback-logic-for-u

MCP Input Analyzer の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

MCP Input Analyzer のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

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.

「開発者ツール」の他のコンテンツ

dxpert UNS tools

dxpert-ai

MCP server for industrial namespace validation — Sparkplug B linter, UNS convention checker, and a free AI-readiness diagnostic. No API key required.

Moxie Docs

Jackalope-Dev

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

Total CMS

Joe Workman

Read-only Total CMS docs and site content over MCP: exact Twig signatures, field types, schema options, the CLI, release notes and comparisons. No key required.

Foremerge

naw103

Catch intent conflicts before code conflicts. The open-source coordination protocol for coding agents, built above Git.

Final POS – Custom POS Builder

Final Commerce

Build custom POS apps with your AI agent. Final's MCP server lets developers scaffold checkout flows, adapt vetted screen blueprints for counter POS, self-checkout kiosks, restaurant ordering and payment terminals, previ