"Understanding Perl, Language Server Protocol (LSP), and Abstract Syntax Trees (AST)" 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.

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.

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.

Integrates Xiaomi MiMo's multimodal API to enable understanding of images, audio, and video through natural language prompts.

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.

Provides JavaScript/TypeScript code intelligence via LSP, enabling goto definition, hover info, and find references through MCP tools.

An MCP server for interacting with the Rell Language Server Protocol interface. It enables LLMs to query LSP Hover and Completion providers for Rell projects.

Enables AI assistants to query and analyze Rell code via Language Server Protocol features like hover information, completions, diagnostics, and code actions. Automatically manages the Rell LSP server and provides resource-based access with real-time subscriptions.

Enables AI coding agents to efficiently explore codebases by providing structural outlines, module digests, symbol bodies, and AST-aware grep via MCP.

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.

MCP server for agentic interaction with the Lean theorem prover via LSP, providing tools for understanding, analyzing, and interacting with Lean projects.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

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

Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables LLM agents to interact with the Lean theorem prover through the Language Server Protocol, providing tools for analyzing Lean projects, accessing diagnostics, goal states, documentation, and searching for theorems using both local and external search services.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

A Model Context Protocol (MCP) server that provides Dart language analysis capabilities to Claude Code, enabling real-time diagnostics, code navigation, and symbol search for Dart projects.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

A comprehensive MCP server for managing AI-assisted Dungeons & Dragons campaigns, featuring tools for character sheets, combat tracking, and world-building. It enables players and DMs to interact with 5e game mechanics and query personal PDF rulebooks using RAG capabilities.