"Ray" matching MCP servers:

Enables AI assistants to understand and navigate codebases through structural analysis. Provides code mapping, symbol search, and impact analysis using ast-grep for accurate parsing of Python, JavaScript, TypeScript, and Go projects.

A local-first MCP server that indexes code repositories and enables AI assistants to search, fetch, and navigate code using BM25 hybrid retrieval, supporting common languages and tools like Codex and ChatGPT.

Local repo-intelligence MCP for coding agents: indexes source, symbols, call graphs, git/GitHub history, and source-bound repo memories into local database.

A powerful Model Context Protocol server that creates intelligent graph representations of your codebase with comprehensive semantic analysis capabilities, supporting 11 languages and 26 MCP methods.

An MCP server that ingests Spring Boot REST microservices from GitHub, builds a request-flow ontology, and enables natural-language queries about code with flow-aware answers and citations.

Enables coding agents to search local repositories through hybrid keyword and embedding retrieval, read matched chunks, and list indexed repos via MCP, without API keys or cloud services.

Enables evidence-grounded diagnosis of Python defects and security vulnerabilities, providing structured reports with vulnerability type, CWE, risk level, root cause, and remediation guidance.

Provides MCP tools for searching a codebase with exact file:line citations, reading specific source spans, and inspecting index stats, enabling agents to retrieve and cite code accurately.

Enables AI assistants to perform hybrid semantic and lexical code search across multiple repositories, retrieve symbol definitions and call hierarchies, and manage repository relations through MCP tools.

Enables LLM agents to efficiently understand and navigate a codebase by providing semantic search over symbols and a reference graph, replacing expensive grep/glob calls with structured tools like definition lookup, caller/callee queries, and change-impact analysis.

Enables natural language search over indexed codebases with source citations and incremental indexing.

Enables semantic search and call-graph exploration over decompiled Unity Mono C# codebases, with hybrid retrieval, LLM re-ranking, and lazy-loaded project indexes.

A semantic code search MCP server that enables natural language queries against your codebase, supporting features like related file discovery and context expansion, all running locally.

Enables semantic search and retrieval of code files using embeddings stored in PostgreSQL. Supports intelligent codebase exploration through natural language queries, file listing, and content retrieval.

AI modifies a function but misses 5 callers that also need updating. crag fixes this — it builds precise call graphs via static analysis, so AI knows exactly what's affected before making changes.

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

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

MCP server that migrates SAP Module Pool programs to RAP applications interactively, using AI and SAP ADT REST APIs with human approval at each step.

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.

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.