"A server for finding code examples on GitLab using semantic search" matching MCP servers:

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

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 semantic search over documentation stored in a Vectorize database using the Cloudflare Agents SDK, allowing users to query indexed content via natural language.

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 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.

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 natural-language semantic search of a project's code through a local vector index, so questions that plain grep cannot match return ranked file:line references. It also indexes or refreshes projects on demand, reports index status, and optionally flags near-identical code across files.

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.

Enables semantic search over local markdown specs, RFCs, and docs using Ollama and LanceDB, allowing AI agents to find relevant information by meaning rather than exact keywords.

First gitlab mcp for you, building together

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables semantic code search across local projects and Git repositories using AI embeddings with ChromaDB. Supports both OpenAI and local Ollama models for private, enterprise-ready code analysis and similar code discovery.

Enables natural language interactions with GitLab via Claude Code, supporting MR reviews, issue management, pipeline monitoring, and branch comparisons.

A production-ready MCP server for GitLab enabling AI assistants to read and manage GitLab projects, merge requests, issues, pipelines, wikis, releases, and more through a unified interface.

Enables AI assistants to interact with GitLab merge requests, review code changes, search projects, and create draft comments for code review workflows.

A Model Context Protocol server for self-hosted GitLab instances, enabling users to manage issues, merge requests, pipelines, and more via Claude Code.

Enables AI agents to query and manage GitLab projects, issues, merge requests, and file contents via the GitLab REST API v4.

A comprehensive GitLab MCP server that enables AI clients to manage projects, merge requests, issues, pipelines, wiki, releases, tags, and milestones through multiple transports and authentication methods.

Enables AI agents to access and act on web, desktop, and mobile interfaces via semantic accessibility trees, using MCP tools for querying, navigating, and executing deterministic UI actions without relying on screenshots or pixel coordinates.