An advanced MCP-based AI agent system with intelligent tool orchestration, multi-LLM support, and enterprise-grade reliability features like semantic routing and circuit breakers.
AI-native orchestration layer with 80+ tools for task management, code editing, browser automation, terminal control, and persistent memory across CLI, local MCP, and cloud deployments.
Enables autonomous orchestration of vector search, knowledge graph queries, and web crawling through a single MCP interface, providing agentic RAG capabilities for AI assistants.
Enables enterprise multi-agent decision workflows that expose 8+ MCP tools such as SQL query, web search, Python sandbox, RAG, file access, data cleaning, chart generation, and HTTP calls, orchestrated with LangGraph, streaming output, and human-in-the-loop approvals.
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).
An enterprise MCP server that exposes 16 standardized tools for document intelligence, RAG, knowledge graph, SQL analysis, LLM evaluation, cost estimation, and AI architecture design, enabling AI agents to securely access and compose enterprise AI capabilities.