Discover verified Model Context Protocol servers to extend your AI assistants. Install configs for Claude Code, Cursor, VS Code, and more.
Browse 260 MCP servers across databases, communication platforms, cloud providers, DevOps pipelines, analytics services, and version control systems. Each server entry includes verified compatibility badges, GitHub star counts, transport type, install commands, and security notes. The Model Context Protocol (MCP) is an open standard that lets AI assistants like Claude, Cursor, and GitHub Copilot interact with external tools and data sources through a unified interface — find the right server to connect your AI workflow to the services you already use.
Connect your AI assistant to Langfuse for LLM observability and debugging. This MCP server enables querying traces, analyzing prompt performance, reviewing evaluation scores, and managing prompts directly from your coding environment. Debug production AI issues by searching traces by user, session, or error status. Compare prompt versions and their metrics side-by-side. Monitor cost trends and latency patterns without leaving your editor. Particularly useful for AI engineers who manage Langfuse-instrumented applications and want to investigate issues inline.
Investigate and resolve Sentry error reports directly from your AI coding assistant. Search issues by error message, stack trace, or affected user. View detailed event data including breadcrumbs, context, and device info. Assign issues, update status, and add comments. The server provides deep integration with Sentry's issue tracking — your AI can correlate errors with recent code changes, identify patterns across related issues, and suggest fixes based on stack traces and surrounding code context.
