"Converting User Requirements to Technical Specifications" matching MCP servers:

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Tells you how you and your Claude agent actually work together. Reads CLAUDE.md, hooks, skills, memory + scheduled tasks and writes you a letter. Local-only, no API keys, no data leaves your machine.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

A ruthless, read-only code review MCP server that analyzes code produced by AI coding assistants, catching missing requirements, security vulnerabilities, edge cases, and performance issues without ever modifying files.

An MCP server that exposes Swarm's fact reconciliation to AI agents, allowing them to query scope, evidence gaps, and review requirements without being able to issue a final verdict.

Enables parsing, validating, and translating POEM pseudo-code specifications into code in any programming language via natural language.

A technical interviewer that ingests GitHub repos, teaches you your own code, and conducts mock interviews with persistent memory of your weak spots.

Enables LLMs to systematically develop and validate regex patterns by defining test cases with expected matches, testing patterns against them, and iteratively refining until all requirements are satisfied.

Enables comparing Ruby hash literals and converting Ruby hashes to JSON with deterministic diff reports, running locally for privacy.

Enables AI coding agents to verify code against YAML specifications, detecting missing fields, extra fields, and type mismatches to prevent silent drift before commits.

Multi-perspective code analysis using Claude Code, Codex, and Antigravity CLI agents to provide direct, honest technical feedback on code, architecture, and ideas.

Enables Claude to consult GLM-4.6's architectural intelligence for system design, code analysis, scalability patterns, and technical decision-making. Provides specialized tools for enterprise architecture consultation, distributed systems design, and code review through the Model Context Protocol.

A server for analyzing technical debt across multiple programming languages, integrating with MCP-compatible tools to detect code quality issues and provide prioritized recommendations.

An MCP server that enables AI to interact with the private 'my-design' React component library and design tokens for UI generation and technical support. It provides tools for component searching, API documentation retrieval, and migration guidance based on specific internal design specifications.