Enables running durable, traceable AI agents via LangGraph through a universal MCP interface, integrating with Hatchet for orchestration, logging, and retries. Provides tools for knowledge management (ingestion, RAG) and Kubernetes operations (diagnosis, auto-fix).
Harness-agnostic MCP server for orchestrating deterministic, resumable multi-agent workflows. It lets you start, watch, resume, and cancel agent runs from any MCP client, using agents from Codex, Claude, Cursor, or Kimi.
An MCP server that exposes deterministic workflows as tools, allowing small models to reliably orchestrate APIs and other MCP servers with minimal parameters.
An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.
MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.