"MiniMax MCP (Model Context Protocol) GitHub Repository" matching MCP servers:

Enables natural-language analysis of GitHub repositories by exposing repository metadata, source code retrieval, search, and file reading as MCP tools, with answers grounded in the actual repository content.

A Python-based server for managing and analyzing code context for AI-assisted development. Provides real-time code analysis, project structure analysis, dependency tracking, and secure API endpoints.

Enables MCP-compatible LLM clients to retrieve repository metadata, list and read files, search code, and fetch README content through natural-language requests.

Enables AI clients to inspect Python repositories read-only through eight MCP tools that expose symbols, cited source excerpts, import dependencies, and supported static caller relationships without importing or executing the code.

Enables large language models to explore, inspect, and analyze GitHub repositories through natural-language queries, using MCP tools to retrieve repository data, file structures, file contents, and code search results from the GitHub REST API.

Provides intelligent codebase analysis, dependency scanning, architecture detection, security vulnerability scanning, and automatic documentation generation for modern development teams.

Enables users to profile public GitHub repositories via a single tool, checking for Spring/Java structure such as pom.xml, src/main/java, Java file counts, and Spring layer annotations to assess suitability for deep local analysis.

Enables querying Odoo's model registry (fields, inheritance, methods) without a database connection by loading the registry in-memory.

MCP server exposing GitHub tools for issues, pull requests, and code browsing via the GitHub REST API. Designed for local LLM clients with flat arguments and streamable HTTP support.

Enables read access to GitHub source code, including code search, file contents, symbols, and Java-aware fragment extraction, with optional per-call repository overrides.

Read-only repository context explorer for coding agents. Provides repository exploration tools via CLI or MCP adapter.

Enables self-hosted, read-only remote interaction with GitHub repositories, allowing listing repositories, searching code, and inspecting commits, pull requests, issues, and diffs via authenticated MCP clients.

Enables AI-powered GitHub interactions including repository analysis, code search, PR reviews, and more through the MCP protocol.

Enables AI coding agents to automatically compile the most relevant slice of a repository into context for a given task.

Provides AI agents with secure, read-only file system access to analyze and understand project codebases, enabling multi-repository context aggregation and cross-project code tracing.

Enables GitHub repository analysis including health score, comparison, commit heatmap, and trending MCP servers, with interactive widgets.

Enables repository context packing, file/symbol ranking, task-relevant selection, and applying structured patches via MCP.

Enables AI agents to search repositories, inspect files and code, list issues and commits, check releases, and look up GitHub user profiles through the GitHub public REST API without authentication.

Stateless Streamable HTTP MCP server exposing 5 GitHub tools (user info, repository metadata, file contents, issue listing, and issue creation) with token-based authentication required only for tool calls.

Provides four GitHub superpowers (repo-scorecard, compare-repos, commit-heatmap, trending-mcp) as MCP tools with React widgets for repository health analysis, comparison, commit activity visualization, and trending MCP servers.

A local MCP server that indexes a repository into line-range chunks and serves compact evidence packets to cut token usage when exploring or debugging code.

MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.

A Model Context Protocol server that connects GitHub code to Claude.ai. This server utilizes the Pera1 service to extract code from GitHub repositories and provide better context to Claude.

Enables AI-driven semantic code search using Windsurf's reverse-engineered SWE-grep protocol to query local codebases with natural language. It executes local search tools like ripgrep and tree-node-cli to return relevant file paths and line ranges to MCP-compatible clients.

An MCP server that turns any public GitHub repository into a PDF report containing a codebase summary, the most recent commits, and suggested improvements — generated locally by an Ollama model.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

Enables AI agents to analyze public GitHub repositories directly through tools for repo health scoring, recent commit summaries, good first issue discovery, and semantic Q&A over docs and issues.

MCP server that inspects local codebases and generates source-grounded context packs for coding agents, with tools for repository search, symbols, dependencies, Git analysis, and context generation.