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

Enables AI assistants to search and analyze codebases using Abstract Syntax Tree (AST) pattern matching with ast-grep. Supports structural code search, pattern testing, and AST visualization across multiple programming languages.

This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.

AST-targeted code editing MCP server with 28 surgical tools for structural edits across 11 languages. Built on tree-sitter, replaces brittle search/replace with byte-correct edits keyed by symbol names.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

Provides deep structural analysis of Python source code via AST, including function signatures, call graphs, cyclomatic complexity, code smells, dead code detection, and protocol conformance.

Provides deterministic Python codebase symbol exploration using AST parsing, with tools for definition lookup, signatures, references, call chains, and class hierarchy queries.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

A robust, language-agnostic Model Context Protocol (MCP) server that provides AI coding agents with the ability to edit files surgically via Abstract Syntax Trees (AST) instead of relying on token-heavy, brittle search-and-replace or diff operations.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

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.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

A self-hosted semantic code retrieval MCP server that enables natural language queries to find relevant code snippets using Tree-sitter AST parsing, embedding, and hybrid search with reranking.

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.

Enables structural code retrieval over MCP by parsing source with tree-sitter and serving symbols, outlines, schemas, docstrings, imports, and AST queries instead of entire files.

A lightweight MCP bridge that lets Claude Code delegate heavy tasks to the Antigravity CLI - saving context window and tokens for what matters.

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

Enables Claude to list directories, read text files, and search code within a designated read-only project folder, while skipping common dependency folders and blocking sensitive files.

A comprehensive MCP server that provides AI assistants with tools for file system management, Git integration, and shell command execution. It features specialized code utilities for analysis, formatting, and linting to enhance development workflows within Claude Desktop.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

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

A code review tool that generates detailed HTML review documents by comparing branches or commits, with author filtering and intelligent analysis.

Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.

Enables multi-agent council workflows for coding assistants, providing parallel independent reviews, plans, brainstorms, validation, and research with strict read-only boundaries.