"Google search or related query" matching MCP servers:

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.

Semantic + lexical code search as an MCP server. Agents query in natural language and get back ranked file:line ranges to read precisely.

Exposes Cursor's semantic code search through MCP, enabling tools like codebase_search to query indexed repos.

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.

Allows Claude Code to request an independent code review from Google Antigravity (Gemini, Claude, or GPT-OSS) via the Antigravity CLI, providing a second opinion on plans or diffs.

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.

MCP server for searching code via SourceGraph's GraphQL API, enabling fast symbol and text search across local or cloud SourceGraph instances.

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

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.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Provides semantic vector search over local codebases via MCP, enabling hybrid search (dense + sparse + RRF) for any MCP client like GitHub Copilot or Claude Desktop.

MCP server for semantic code search with AST-aware chunking, hybrid vectors, and query syntax.

Enables AI coding agents to preflight SQL, NoSQL, graph, warehouse, and vector queries against real schemas or pasted DDL, estimating cost/risk, suggesting verified rewrites, and explaining plans before execution. It supports 12 database engines and catches costly query patterns without running the query.

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.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

Enables AI agents to query Linux kernel source code, git history, LKML discussions, Patchwork patches, and documentation with evidence-ranked results, citations, and explicit assumptions or contradictions.

Enables token-efficient structural code exploration using tree-sitter AST parsing, with tools for symbol search, outlines, source unfolding, call graphs, and related-file discovery.

Show an AI coding assistant only the code that matters for a change — callers, callees, and related functions packed into a token budget, with self-grading retrieval.

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

Instant, code-aware local search engine

Enables AI coding agents to check PyPI and npm packages for sandbox-verified outdated-code corrections, search errors by text or traceback, and submit confirmation or dispute reports.

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.

An MCP server that indexes TypeScript/JavaScript codebases into precise call and import graphs using the TypeScript compiler API, allowing Claude or any MCP client to query definitions, callers, callees, and perform impact analysis.

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.

Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.