A comprehensive Model Context Protocol (MCP) server that exposes 216 tools, 7 resources, and 10 runbook prompts for every OpenShift 4 cluster operation an SRE, developer, or operator could need — all driven by an LLM.
A local-first LLM routing MCP server that keeps sensitive data on your own models, with fail-closed privacy and manager-worker delegation, exposing route and complete tools to any MCP client.
Enables offline AI agent automation with embedded local LLM (Qwen 2.5), sandboxed file operations through AgentFS, and dynamic skill loading. Exposes capabilities via MCP with tri-state safety guards for private, air-gapped environments without network connectivity or API costs.
Unified MCP server for managing local model runtimes (Ollama, LM Studio, etc.), enabling provider-agnostic discovery, lifecycle management, hardware-fit checks, and delegated inference.
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Creative Commons Attribution Non Commercial No Derivatives 4.0 International
A modern Model Control Plane (MCP) project that provides a lightweight, extensible foundation for building and deploying intelligent systems that manage and expose AI/LLM capabilities through Python, FastAPI, and Docker.
Universal MCP router and gateway that bridges LLM agents to OpenAPI, GraphQL, and AWS Lambda services with ISO/IEC 42001 AI governance, RBAC, PII redaction, semantic tool routing, and a web dashboard.
