"Understanding Abstract Syntax Trees (AST)" matching MCP servers:

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

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

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 providing vision understanding tools (image QA, OCR, video and document understanding) via OpenAI-compatible endpoints, defaulting to Zhipu GLM vision models.

A Model Context Protocol (MCP) server for validating Mermaid diagram syntax and providing comprehensive grammar checking capabilities

Base library for building MCP e-invoicing servers: abstract base classes, shared Pydantic models, XML utilities, and OAuth2-capable async HTTP client.

Provides AI assistants with progressive code intelligence to explore repository structure, find symbols, and assess the impact of changes using ast-grep.

Provides vision capabilities to text-only LLMs by acting as a cloud vision adapter layer, enabling image understanding and OCR text extraction through a single MCP tool.

Local MCP server for semantic code search using Tree-sitter AST parsing, local embeddings, and hybrid search; enables indexing and querying codebases entirely offline.

The MCP server for Nanostores that scans your codebase with AST analysis to find stores, subscribers, and dependency chains, and can ingest live events to spot noisy, error-prone, or unused stores.

Provides comprehensive Pine Script v6 documentation and tools to help AI assistants look up functions, validate syntax, and generate accurate code. It enables linting, version conversion from v5 to v6, and deep conceptual analysis to prevent code hallucinations.

An MCP server that enables MCP clients to directly access and process arXiv papers by fetching the LaTeX source, improving mathematical content understanding.

Renders source code as beautiful SVG or PNG images with syntax highlighting, line numbers, and diff support. Ideal for AI agents to present code visually to humans or for sharing snippets.

Generates Excalidraw architecture diagrams with support for 60+ components including GCP, Kafka, and AI/Agentic shapes. Provides MCP tools for creating, modifying, and converting diagrams from structured input or Mermaid syntax.

Enables searching X (Twitter) using the xAI Grok API to get summarised answers with citations. Supports filtering by handles, date range, and image/video understanding.

Context+ is a semantic intelligence server that transforms codebases into searchable, hierarchical feature graphs using RAG, Tree-sitter AST, and spectral clustering. It provides tools for deep code discovery, blast radius analysis, and memory graph management for high-accuracy engineering tasks.

SQL Server MCP server with AST-based query validation, read-only safety, schema exploration, ER diagram generation, and DBA toolkit integration (First Responder Kit, DarlingData, sp_WhoIsActive).

Local-first MCP server that gives AI agents token-efficient context from any codebase: project tree, search, and budgeted packs. Secret redaction is enforced by the server, Git scopes and syntax-aware compression keep packs small. The same engine ships as a GUI, TUI, and CLI.

An MCP server that generates ranked, token-budgeted code structure maps using Tree-sitter AST analysis and PageRank, enabling AI agents to quickly understand unfamiliar codebases.

Security, cost, and health governance proxy for MCP infrastructure. Enforces YAML-configurable security policies (blocklists, rate limits, token budgets), tracks real token costs via tiktoken, monitors server health with live JSON-RPC probes. Features OAuth 2.1/OIDC with RBAC, web dashboard, payload normalization, semantic shell AST analysis, mTLS, and a formal STRIDE threat model.