"Trending MCP server for memory usage with GitHub Copilot integration" matching MCP servers:

Enables GitHub Copilot to perform markdown review, dependency checking, and AI-powered code review through serverless Azure Functions, demonstrating educational and production MCP tool patterns.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Integrates GitHub Copilot CLI with MCP clients to offer various coding assistance tools including asking questions, explaining code, suggesting commands, debugging, refactoring, generating tests, and reviewing code.

Integrates GitHub Copilot with MCP-compatible tools to provide AI-powered code assistance, including chat, code explanation, and reviews. It leverages existing GitHub CLI authentication to support multiple models like GPT-4o and Claude 3.5 Sonnet.

Connects MCP-enabled editors to GitHub Copilot CLI for non-interactive code analysis, batch processing, and code review.

A radare2 MCP server for binary analysis and reverse engineering, enabling AI agents to interact with radare2 through natural language or structured commands for tasks like static analysis, debugging, and patching.

Enables MCP-based hybrid semantic code search over repositories, providing tools for searching code by meaning or keyword, retrieving symbol definitions, finding usages, reading chunks, and listing indexed repos.

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.

MCP server for diagnosing Apollo InMemoryCache normalization defects, providing cache analysis and repair planning tools for React Native apps.

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 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 MCP clients such as Claude Desktop and Claude Code to query an indexed source repository through path-guarded tools for hybrid keyword-and-vector code search, file snippets, symbol explanations, reference lookups, and test-skeleton suggestions. Serves those results over stdio with cited file:line locations so agents can answer questions about a codebase and drive grounded code review.

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

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.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

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.

Long-term memory for AI coding agents, stored as a tree of plain local files. Agents search it before answering and save what lasts; changed facts are kept as history and flagged as outdated.

MCP server for exploring GitHub public data. It provides tools to fetch user profiles, list top repositories, and calculate language usage statistics, which AI agents can invoke dynamically.

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.

A stateless MCP server that gives coding agents a curated entry point to shared memory, orchestrating Hindsight (facts) and LightRAG (corpora) for automatic routing, URL ingestion, and consistency tooling.