claude-flow
Verified · 2 days agoAI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
MCP server for Langfuse LLM observability — trace and observation analysis.
claude mcp add langfuse -- npx -y [email protected]
Read-only Langfuse trace inspection: four tools (get_traces, get_trace_detail, get_observations, get_observation) for debugging LLM pipelines and analyzing cost/latency, with a practical token-saving touch — any payload field over 1000 chars is truncated to a /tmp file with a grep-able reference. It requires Langfuse public and secret keys and defaults to Langfuse Cloud, though self-hosted instances work via LANGFUSE_BASE_URL. Like the remote-filesystem sibling it lives in the 'experimental' tier of PulseMCP's monorepo — explicitly not graduated to their productionized set — and adoption is thin (~73 weekly downloads). For teams already on Langfuse who want an agent to dig through traces; the read-only design keeps the blast radius small.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
Draw and visually collaborate with your agents on tldraw's canvas.
Codebase knowledge graph for AI agents — 159 languages, sub-ms queries, 99% fewer tokens.
Official OpenMetadata MCP: governed context and business semantics for AI assistants and agents.
Control real Android and iOS devices with LLM agents — tap, swipe, type, automate flows.
AI Agents Framework with Self Reflection and MCP support