MCP server for Langfuse LLM observability — trace and observation analysis.
- 来源
- MCP 注册表
- 领域
- 智能体、技能与 MCP
- 用途
- 可观测性
与可观测性相关的已测量目录条目。
MCP server for Langfuse LLM observability — trace and observation analysis.
Creating realistic RL environments requires collaboration between researchers, engineers, and domain experts across many dimensions: artifacts, environments tools, dynamism of the environment, reproducibility, and more. There is no open source framework for building these environments effectively. Until now.
A Claude Code mod that puts a live agent dashboard in your terminal: context and cost, advisor timeline, every permission check, subagent cards and swimlanes.
A typed, replayable, budget-aware programming language for LLM agents. Compiles to Python & TypeScript.
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative configs with command line and CI/CD integration. Used by OpenAI and Anthropic.
Mastra is the modern TypeScript framework for AI-powered applications and agents.
The fastest path to AI-powered full stack observability, even for lean teams.
Open source observability platform for logs, metrics, traces, RUM (web, android, ios), Session replay, pipelines, SLO and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.