"How to use Google Search" matching MCP servers:

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enables SDK and MCP clients to perform repository code search and retrieval, inspect current source and related evidence, and optionally use semantic search, reranking, and web sources while keeping the calling agent in control.

A FastMCP server for bounded, keyword-driven repository context search, enabling efficient codebase exploration with snippet extraction and focused code block retrieval.

Provides a code search service via MCP, allowing AI clients to perform fast, indexed searches across large codebases using Zoekt, with support for filters like repository, language, and path.

Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Enables AI agents to perform semantic code search across entire codebases using natural language queries. Provides fast indexing and ranked search results with line numbers and file paths through the Seroost search engine.

Clones a Git repo into a temp directory so MCP clients can search and read files from another repo for context.

An MCP server that edits files through a real Neovim instance, giving agents access to LSP diagnostics, formatting, code actions, and plugin commands.

Enables AI coding assistants to semantically search codebases by meaning rather than exact text, with zero external daemons and fully local embeddings. Works out-of-the-box with Claude Code, Gemini CLI, Antigravity, and Cursor.

Integrates Google Gemini 3.1 with Claude Code to provide web search, large codebase analysis, multimodal image understanding, and creative brainstorming, leveraging Gemini's 1M token context and Google Search grounding.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

locidx

Translate Python between English and your language, with round-trip verification. Pack-based and reviewed, not model-guessed: translate files both ways, look up how terms render, check identifier names, and report how legible a codebase is in a language, all locally with uvx legesher-mcp.

Instant, code-aware local search engine

Self-hosted semantic code search for AI coding agents. Indexes many repositories at once with tree-sitter AST chunking, local llama.cpp embeddings and Qdrant, so Claude Code, Cursor, Codex and any MCP client can find code by meaning, trace usages and callers, and read the git history behind each chunk. No API keys, and your code never leaves your machine.

Enables AI agents to navigate JS/TS, HTML, and CSS code — symbol info, outlines, callers, implementations, definitions, references, hover, and diagnostics — through bundled Node language servers. It also builds a cross-file index answering where CSS custom properties and #id/.class selectors are defined and used across stylesheets, markup, and scripts.

Local AST call graph and code map for AI coding agents. Finds where to start for a task (ranked files), who calls a method and how far a change ripples, method bodies by line range, string and constant search, and framework views (Laravel routes, validation, events; Vue props and emits). Supports PHP, JS, TS, Vue, Rust, Swift, Python and Go. Runs locally, no API key or account needed.

Combines semantic search with AST-based code exploration for AI agents, enabling natural language code search, file structure browsing, symbol inspection, and dependency analysis through the Model Context Protocol.

Enables AI agents to formally verify constant-time, masking, and patch completeness properties of Verilog hardware designs, providing concrete leakage signals and next-step guidance.

A lightweight MCP server that provides 40 tools for TypeScript/JavaScript refactoring and code intelligence, directly mapping to TypeScript's tsserver protocol commands for accurate structural changes and workspace analysis.

Analyzes code repositories and generates comprehensive documentation published to Google Docs with Mermaid diagrams.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Enables AI coding agents to perform fast regex/text and structural AST searches across codebases, find symbols, list files, and safely preview or apply refactors. It unifies ripgrep and ast-grep with pagination, gitignore-aware defaults, and fallback engines for zero-setup code search.

Provides semantic code search over codebases using local embeddings with natural language queries. Supports hybrid search, file watching, and respects .gitignore.

Semantic code search for Claude Code, enabling natural language codebase indexing and search using AI embeddings.

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.

An MCP server that enables AI agents to move TypeScript files and directories while automatically updating all affected imports using a persistent tsserver instance. This ensures atomic, error-free refactoring that maintains project integrity without manual intervention or wasted tokens.

Enables AI assistants to search, validate, and use UdonSharp documentation and templates for VRChat development via MCP, with live indexing and IDE/agent support.

Exposes TypeScript language service tools (completions, go-to-definition, type info, diagnostics) via MCP for use by AI or IDE clients.

Analyzes JavaScript/TypeScript projects for code modernization opportunities, checks browser compatibility via Can I Use, searches MDN documentation, and recommends modern Web API alternatives to reduce bundle size and improve performance.

Enables semantic code search across local projects and Git repositories using AI embeddings with ChromaDB. Supports both OpenAI and local Ollama models for private, enterprise-ready code analysis and similar code discovery.

An MCP server for indexing and querying Unreal Engine C++ codebases using a local SQLite database. It enables users to analyze call graphs, class structures, and Blueprint-exposed symbols through tools integrated with Claude Code.

Enables intelligent code analysis and search across repositories using the CodeRank algorithm (inspired by PageRank) to identify critical modules, trace dependencies, find code hotspots, and perform context-aware keyword searches with importance-ranked results.

Automatically collects, summarizes, and documents code from vibe coding sessions, generating multiple document types (README, DESIGN, TUTORIAL, etc.) and publishing them to platforms like Notion, GitHub Wiki, and Obsidian.

Enables searching and browsing Android source code across projects like Android, AndroidX, and Android Studio via cs.android.com. It provides tools for regex-based code searches, full file content retrieval, and symbol autocomplete suggestions.

Enables local language models to request real-time peer review feedback from Google Gemini to improve response quality, accuracy, and completeness through AI collaboration.

Enables Claude Code to use Google Gemini AI capabilities for analyzing PDFs and images, generating and translating text, and reviewing code. Supports both CLI and API backends with different quota limits.

Enables full-stack compiler development across the hw-native-sys workspace by combining repository operations (git health, code search, task running) with a knowledge layer for architecture docs, task routing, and abstraction/pass pipeline information.

Helps AI read GitHub repository structure and important files. Want to quickly understand what a repo is about? Prompt it with "read https://github.com/adhikasp/mcp-git-ingest and determine how the code technically works".