A FastMCP server that provides LLMs with structured access to Scalene's CPU, GPU, and memory profiling for Python applications. It enables automated performance analysis, bottleneck identification, and optimization suggestions through natural language interactions in supported IDEs.
An MCP server that converts Windows WPR .etl performance traces into structured JSON summaries and flamegraph-ready data for LLM analysis. It bridges Windows Performance Analyzer automation with LLM reasoning capabilities for performance troubleshooting.
An MCP server that connects Claude (or any MCP compatible client) to your existing log infrastructure. Query, summarize, and trace logs in plain English across GCP Cloud Logging, AWS CloudWatch, Azure Log Analytics, Grafana Loki, and Elasticsearch without writing filter expressions or leaving your editor.
MCP-native LLM observability. Query your Spanlens traces, stats, cost anomalies, and savings from Cursor, Claude Desktop, or any MCP client. Open source (MIT).
MCP server that exposes llm-tldr code analysis tools (tree, structure, context, search, impact, etc.) to MCP clients like Claude Code for project understanding and debugging.
