"A tool for finding academic papers using semantic search and citation analysis" matching MCP servers:

Enables AI coding agents to perform semantic code search locally, finding code by meaning rather than exact keywords.

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

Enables semantic code search over local repositories, providing tools like semantic_search and list_indexed_repos to Claude Code, so users can find relevant code sections via natural language instead of grep.

Enables AI agents to perform semantic search over codebases by converting natural language queries into efficient search patterns like grep and ripgrep. It utilizes LLMs to verify relevance and find code snippets that traditional keyword-based searches might miss.

Provides AI coding agents with structured access to indexed codebases via semantic search, symbol analysis, and file reading tools.

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.

A 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.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

A 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.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

Enables AI coding agents to test C++ code by running static analysis, sanitizers (ASan, TSan, LSan, UBSan), and performance profiling through eight MCP tools.

Provides structured semantic context for JavaScript/TypeScript codebases, enabling coding agents to navigate, review, and change code with explicit uncertainty.

An MCP server that provides six code review tools for use with Claude Code or any MCP client. Each tool reads a file from disk, pairs its contents with a structured review prompt, and returns the bundle for the LLM to evaluate.

Provides worktree-aware semantic code indexing and search via MCP, enabling agents to query indexed code and monitor indexing status while keeping lifecycle operations separate.

A modular MCP server for code analysis using ast-grep, enabling structural pattern matching and transformations across multiple languages.

A local MCP server that provides Sonar-grade static analysis (bugs, vulnerabilities, code smells) for TypeScript/JS and C# repositories, with CLI and dashboard support.

MCP server for persistent project knowledge management, enabling AI assistants to store, search, and reuse project analysis insights with freshness checking and impact analysis.

Builds a semantic knowledge graph of C++ code and exposes 9 MCP tools for AI assistants to search classes, functions, inheritance, callers, callees, overrides, and more.

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

Provides hybrid semantic and keyword code search for Claude Code using BM25 and vector retrieval. It enables indexing and searching local codebases with language-aware chunking and local embeddings.