6 个#tracing MCP 服务器和客户端

A Playwright-based MCP server that exposes a live browser as a traceable, inspectable, debuggable and controllable execution environment for AI agents.

Langfuse MCP

therealsachin

Production-ready Langfuse MCP Server with 28 tools for LLM analytics, cost monitoring, and dataset management. Features secure dual-mode operation (readonly & readwrite), real-time cost analysis, trace debugging, and comprehensive usage insights. Deploy instantly with npx for sea

Ingero

ingero-io

eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime/Driver APIs and host kernel events to build causal chains explaining GPU latency

The first MCP-native eval and observability tool for AI agents. Any MCP-compatible agent discovers and uses Iris automatically — no SDK, no code changes. Log traces with hierarchical span trees, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost

Agentops Mcp

AgentOps-AI

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.