W&B MCP SERVER
Power AI agents with full context of your experiments and traces
W&B Model Context Protocol (MCP) server turns your AI agent or IDE into an expert on your W&B workflow. It gives agents efficient, programmatic access to your experiments, traces, reports, registries, and documentation, so they can analyze runs, debug agents, generate reports, version and manage model artifacts, and get help integrating your applications with W&B features with minimal token usage.
W&B MCP server integrates natively with popular IDEs, chat and coding agents including Claude Code, Cursor, Codex, Gemini CLI, VS Code, and more, with both hosted and self-managed deployment options.
What can your agents do with knowledge from W&B MCP server?
W&B MCP server connects agents with data, experiments, traces, reports, and documentation from your W&B Workspace
Analyze experiments
Query, compare, and diagnose W&B Models runs to identify metric trends, regressions, failures, and experiment insights.
Track agent behavior
Query and aggregate W&B Weave traces, LLM calls, agent runs, failures, latency, and evaluation results to understand behavior and performance.
Create reports
Generate W&B reports automatically to summarize experiment results, evaluations, and agent behavior.
Manage and version models
Inspect, compare, and manage model versions and datasets across W&B Registry and Artifacts.
Get expert W&B guidance
Give agents direct access to W&B documentation so they can answer product questions and help troubleshoot integrations.
Benefits of using W&B MCP server
Faster iteration cycles
Query experiments, traces, and evaluations directly from your IDE or agent so you can analyze results, debug issues, and iterate faster.
Higher team productivity
Reduce repetitive debugging, reporting, and investigation work by giving agents direct access to your W&B workspace and documentation.
Instant W&B expertise
Connect agents to W&B docs and workspace context so they can answer product questions, troubleshoot integrations, and generate more accurate responses.
Better agent reliability
Use structured experiment and trace data to help agents identify regressions, analyze failures, and improve application performance over time.