"Enhanced MCP-Reasoner with Monte Carlo Tree Search and Beam Search Integration" matching MCP servers:

Exposes Beam's local, offline risk-scanning tools to any MCP-compatible host, enabling read-only heuristic detection of risky AI agent patterns without executing, blocking, or approving actions.

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.

Enables semantic code search across indexed code folders using vector embeddings, with support for multiple embedding providers and automatic file watching. Provides an admin UI and integrates with MCP clients for natural language code queries.

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

Enables AI agents and developers to independently verify trading-strategy backtests, detect look-ahead bias, hidden costs, and overfitting, and obtain verdicts with reproducible, optionally signed certificates.

A CLI-first semantic code search tool with MCP integration for AI assistants, enabling semantic search, AST-aware parsing, and code analysis across 13 languages.

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.

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.

Enables LLM agents to navigate source code structurally via tree-sitter over MCP, offering outline-based reading, AST pattern search, workspace-scale symbol indexing, call graph analysis, and built-in security audit queries.

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 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.

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.

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

Enables token-bounded, read-only hybrid code search across local repositories by fusing literal matches with AST symbol relations to return high-signal snippets, line ranges, and call metadata.

Enables cross-repository code search over a local mirror of a self-hosted Gitea or Forgejo instance, covering file contents, file paths, and commit messages across all repositories and branches. It also lets users read a single file from the mirror and list mirrored repositories, all without network access during search or read.

Enables LLMs to perform high-performance code search and analysis across multiple languages using symbol indexing, regex text search, and structural AST pattern matching. It also provides tools for technology stack detection and dependency analysis with persistent caching for optimized performance.

Enables read-only code search in a specified local directory and public web search through the user's own Devin session, with login handled only in the terminal.

An MCP server for semantic code search using Qdrant vector database, enabling natural language queries to find relevant code snippets across indexed codebases.

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

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.

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

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.

An MCP server that indexes source code into a local database and provides tools for querying code symbols, dependencies, and tree structure for JavaScript/TypeScript, Java, and Python.

An MCP code-intelligence server for AI agents with pre-indexed AST cache, 62 MCP tools, and TOON-compressed output, enabling token-efficient code analysis and project health grading entirely locally.

A Model Context Protocol (MCP) server that provides code analysis capabilities using tree-sitter, designed to give Claude intelligent access to codebases with appropriate context management.

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