"Using ast-grep to Modify Code Programmatically" matching MCP servers:

Enables autonomous agents to parse markdown into structured AST nodes and compile modified ASTs back into clean canonical markdown, including headings, lists, tables, and code blocks.

Enables autonomous agents to parse markdown documents into structured AST nodes—including headings, lists, tables, callouts, and code blocks—and serialize modified AST back into clean canonical markdown via MCP tools.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Serves bundled local engineering guidance—four instructions, a control Guide and 20 software engineering procedures—over local STDIO so coding agents can discover and read the right procedure for a task. It is read-only and stateless, leaving all project changes and permissions to the consuming agent.

Connects to vibe-code-best-practices.vercel.app to index 817 tools across 185 sections and 10 domains, routes the right tool/Skill for your project need, and can recommend a full stack.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Converts Markdown files to Atlassian Document Format and publishes them to Confluence, with support for rendering Mermaid diagrams as PNG attachments.

Converts any OpenAPI/Swagger spec into an MCP server, exposing REST API endpoints as tools for Claude.

Enables an MCP client to retrieve explicitly allowlisted Markdown context, create and read local task contracts, write local handoffs, and return locally configured routing metadata without invoking a model, executing commands, or writing to the vault.

Enables converting Markdown text into clean HTML for headings, lists, code blocks, tables, links, and images, with optional full-document wrapping via x402 micropayments.

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.

Provides AI agents with a governed, three-layer project memory (guide, code facts, and knowledge) through namespaced MCP tools for code search, context compilation, impact analysis, and proposal-driven documentation updates.

An MCP server that provides static validation and documentation lookup for quantum computing libraries, currently supporting PennyLane. It allows users to verify quantum code syntax and method usage against official library documentation to ensure correct implementation.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Allows LLM tools like Claude Desktop and Cursor AI to access and summarize code files through a Model Context Protocol server, providing structured access to codebase content without manual copying.

Enables local conversion of PDFs to Markdown, with automatic OCR fallback for scanned pages, image extraction, and page-by-page structure preservation.

Searches Claude Code documentation via BM25 indexing, returning ranked snippets with category filtering. Enables fast, local search over official docs without full-document scans.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

Facilitates searching and accessing programming resources across platforms like Stack Overflow, MDN, GitHub, npm, and PyPI, aiding LLMs in finding code examples and documentation.

Provides AI assistants with access to personal best practice skills and coding guidelines stored as markdown files in a GitHub repository, enabling retrieval and listing of custom development standards.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Converts Markdown files and raw content into professionally styled PDFs with full support for Mermaid diagrams and syntax highlighting. It offers customizable page formats, margins, and modern typography for high-quality document generation.

An MCP server that performs code reviews by comparing local source code against design documents stored in Confluence. It integrates with Atlassian MCP servers to analyze documentation and provide suggestions for quality improvement based on design specifications.

Analyzes source code across multiple languages to extract structural elements like classes, functions, and parameters using tree-sitter. It provides LLM-optimized markdown output that includes nesting levels, line numbers, and signatures to facilitate codebase navigation.

Enables document-driven development by automatically detecting Markdown spec changes, generating implementation plans, and syncing code and tests through MCP tools.

Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.

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