"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.

Enables code analysis of JavaScript, TypeScript, TSX, Python, and Rust files using Tree-sitter, providing symbol listing, definition/reference lookup, AST queries, LSP-style features, and SQLite indexing for efficient cross-file searches.

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.

Provides AI agents with local Dutch spelling and word validation using OpenTaal/hunspell, plus detailed word information from woordenlijst.org. It enables checking full texts or individual words and retrieving linguistic details for Dutch writing tasks.

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.

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

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

Enables LLM agents to explore JavaScript/TypeScript repositories through parsed syntax trees by returning compact file outlines, precise symbol definitions, and local dependency graphs. It keeps access read-only and sandboxed to chosen roots while using a bounded, flood-proof stdio transport.

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.

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 that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

Bridges Claude Code to Language Server Protocol (LSP) servers to enable semantic code intelligence features like navigation, refactoring, and real-time diagnostics. It supports multiple languages including TypeScript, Python, and Rust with multi-root workspace capabilities.

Minimal MCP server bridging a Roslyn C# language server to AI agents, exposing tools for diagnostics, call hierarchy, and type hierarchy.

Autonomous DeFi yield for AI agents on Base. Query APY rates, agent status, payment splits, and referral stats. 4 read-only tools + 1 resource.

ast-mcp-server gives coding agents compact, type-aware access to TypeScript and JavaScript projects, providing structural code tools based on the real compiler project model through ts-morph for declarations, references, renames, and diagnostics, with safe prepare → review → apply mutation semantics and immutable hash-bound plans.

Enables AI coding agents to interact with TypeScript projects through compiler-level code intelligence, providing tools for navigation, type information, diagnostics, refactoring, and semantic search.

Connects AI coding agents in the Antigravity CLI to native language servers for C#, C/C++, TypeScript/JavaScript, and Python through MCP tools, enabling precise symbol navigation, diagnostics, references, refactoring previews, and other code intelligence.

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

Provides comprehensive wallet, token, and smart contract utilities for the Abstract Testnet and Mainnet, including balance checks, transfers, and ERC-20 deployments. It enables users to manage Abstract Global Wallets and generate EOA accounts through natural language commands.

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.

MCP server that analyzes TypeScript/JavaScript codebases via AST parsing and dependency graph tracing to identify affected tests, detect dead code, circular dependencies, and trace import chains, enabling AI agents to run only relevant tests.

Trust infrastructure for the agent economy.

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.