Find the right integration tool for any task by searching available actions with semantic search. Describe what you want to do and get relevant tool suggestions.
MIT
520,987 tools. Updated 2026-09-06 09:34
"A tool for searching code using semantic understanding" matching MCP tools:
- Locate OWNERS files for Chromium source code files by searching up the directory tree to identify code reviewers and maintainers.-
- Analyze code files to identify top-level symbols and their structure, providing a quick overview for understanding new codebases or files.MIT
- Sets the delivery address for Uber Eats. Provide a full street address including city and zip code before searching for restaurants.MIT
- Indexes a codebase to build vector embeddings for semantic code search across 50+ languages. Required initial step before searching code.MIT
- Explain code or concepts by providing a snippet or topic with optional context, and receive clear, actionable explanations for learning, documentation, and deeper understanding using GLM.MIT
Matching MCP Servers
- FlicenseAqualityCmaintenanceA local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.33-
- AlicenseAqualityBmaintenanceA self-hosted semantic code retrieval MCP server that enables natural language queries to find relevant code snippets using Tree-sitter AST parsing, embedding, and hybrid search with reranking.12MIT
Matching MCP Connectors
Cloudflare Workers MCP server: code-explainer
- Travel CodeOAuth
Corporate travel: search and book flights, hotels, rail and transfers, manage orders.
- Find code by meaning with hybrid semantic and exact text matching, returning relevant snippets with file locations and line numbers.MIT
- Get all tool categories with their tool counts to survey the available tool landscape before running a search.MIT
- Find code by meaning using semantic search with natural language queries. Combines AI understanding with text matching to locate relevant snippets, handling typos and variations.MIT
- Index a local repository for semantic code search. Scans files, splits them into functions/classes, and generates embeddings for retrieval.-
- Read source code files from a repository for code review, debugging, and understanding implementation details.MIT
- Translates source code into plain English for non-programmers. Ideal for understanding inherited code, due diligence, and onboarding documents. Costs 500 sats via Lightning.MIT
- Extract function names from PureScript code snippets, focusing solely on functions while excluding data types and classes. Ideal for quick code analysis and understanding.MIT
- Search indexed code and documentation using hybrid semantic and keyword retrieval. Ideal for answering questions about your codebase and project architecture.Apache 2.0
- Extract text from screenshots using OCR, ideal for code, terminal output, documentation, and general text.Apache 2.0
- Resolve Git merge conflicts with AI by understanding code intent from both branches. Detect semantic conflicts beyond text, generate tests, and score confidence for auto-application.MIT
- Determines if understanding meets 95% threshold; otherwise code edits remain blocked.MIT
- Search logs using natural language queries with semantic understanding for Kubernetes/Tekton environments. Interprets queries with NLP, recognizes entities, and ranks results by relevance.Apache 2.0
- Search code examples in Collibra documentation using semantic queries. Find scripts for specific tasks with natural language.Apache 2.0
- Build or refresh a directory's semantic index to enable searching and code understanding. Adjust granularity, recursion, file extensions, and ignore patterns to match your needs.MIT
- Search through your indexed local documents and images using semantic understanding to find relevant content.MIT