"A server for finding information about Artificial Intelligence (AI)" matching MCP servers:

A production-grade MCP server providing advanced code intelligence capabilities such as semantic search, dependency analysis, and natural language Q&A across multiple programming languages.

MCP server providing 29 tools across 5 layers for semantic TypeScript/JavaScript code intelligence, enabling AI agents to find references, trace impacts, guard APIs, and explain errors without text-search false positives.

Provides GitHub repository analysis tools for Claude, including repo summaries, commit history, issue tracking, contributor stats, and code quality assessment. Enables natural language queries about code quality, contributor activity, and repository comparisons.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

Provides codebase indexing and retrieval tools that give AI agents token-efficient, query-relevant context packages (symbols, imports, and dependencies) instead of scanning entire repositories.

Hardware-accelerated codebase mapping that indexes Git repositories into Postgres/pgvector and serves code search, relationships, and static analysis results via a stdio MCP server.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

An MCP server that gives LLMs structured, read-only insight into local code repositories — directory tree, languages, dependencies, scripts, and config files.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

A local-first MCP server that gives AI coding agents durable project memory, dependency graphs, and impact analysis to answer team knowledge and cross-file change questions before editing.

Intelligent code search MCP server with AST analysis, call graphs, dependency tracking, and semantic embeddings for developers.

Provides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.

Enables AI coding assistants to ground on real D365 F&O AOT metadata locally and offline, preventing hallucinated X++ field names and Chain of Command signatures.

AI-powered smart contract security analysis for AI agents and developers, enabling scanning of Solidity repos for vulnerabilities.

Indexes Python codebases using AST and BM25, providing 8 MCP tools for code exploration and search.

Enables AI clients to inspect backend systems through structured engineering tools including Git history, Winston logs, OpenAPI contracts, and sandboxed source code.

Enables coding agents to search locally indexed repositories with hybrid semantic and lexical retrieval, returning exact source citations with file paths and line ranges.

AI-powered static analysis for Unity projects, detecting common patterns, component relationships, and programming insights to augment developer workflows.

Enables querying a TypeScript repository's structure (symbols, imports/exports, references) through direct queries, avoiding repetitive grep operations.