"Documentation URL for a service API, data, and LLM usage" matching MCP servers:

Automatically analyzes Python codebases and generates professional documentation including README, API docs, and setup guides.

Generates professional documentation for multi-language projects with deep code analysis, supporting frameworks like Docusaurus, MkDocs, and Sphinx, including API docs, PDF export, and OpenAPI specifications.

Generates professional documentation for multi-language codebases with deep AST-based code analysis, supporting Docusaurus, MkDocs, and Sphinx frameworks. Includes API documentation generation, PDF export, OpenAPI spec generation, and sales-ready documentation for code marketplaces.

Enables onboarding a codebase for AI-agent-assisted development by scanning projects, collecting human-only answers, and maintaining traceable living documentation under .ai/ for both humans and AI coding agents.

Analyzes codebases to automatically generate README, API docs, architecture diagrams, and CHANGELOG.

A smart documentation server that provides AI-assisted code improvement and documentation management through Claude Desktop integration.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

Enables coding agents to inspect Python applications, research source and target models, and produce reviewable migration plans with evidence gates and evaluation before production code changes.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

MCP server for reviewing code changes using LLMs, supporting Copilot, Ollama, and OpenAI-compatible endpoints.

Enables business services to push error logs and generate diagnostic reports using MCP tools for log searching, code querying, and report generation.

Enables scanning repositories for hardcoded service URLs and clients, and building service-to-service API dependency maps.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Scan-as-a-Service for MCP servers. Wraps the compuute-scan static security scanner with HTTP and MCP endpoints to analyze public GitHub repos for MCP-specific vulnerabilities.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

MCP server that exposes an AI decompiler via an OpenAI-compatible API, enabling decompilation, explanation, and variable renaming of disassembly for binary analysis.

Bridges local LLMs running in LM Studio with MCP clients like Claude Desktop to perform reasoning and analysis tasks while keeping sensitive data private. It features a suite of tools for local code review, privacy scanning, and content transformation using auto-discovered local models.

Enables authenticated MCP clients to check adapter status and, when explicitly enabled, run bounded correctness reviews of owner-consented public Python code through an existing gateway while keeping secrets and model calls gated.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

MCP server exposing a shared pr-review skill with tools to list, get, run, and evaluate skills, enabling AI assistants to perform code review tasks.