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agent-mesh-mcp

Coordinate agent communication, cost-aware routing, and deployments on K3s.

1|Updated Apr 3, 2026
Search Tags:#rbac#mcp#ansible#promql#litellm#k3s#agent-mesh
One-click install
npx skills add https://github.com/villadalmine/infra --skill agent-mesh-mcp
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-mesh-mcp
Source: https://github.com/villadalmine/infra/tree/main/.agents/skills/agent-mesh-mcp
Command: npx skills add https://github.com/villadalmine/infra --skill agent-mesh-mcp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you manage a homelab AI control plane where multiple agents, model routers, and cluster services must coordinate without accidental coupling or runaway spend.

Core Features & Use Cases

  • Agent mesh architecture: Describes how OpenClaw, Hermes, and Kubernetes MCP services should delegate tasks across the cluster.
  • Cost-aware routing: Uses Prometheus and LiteLLM metrics to choose economical models and track token spend before expensive operations.
  • Granular deployments: Supports separated Ansible and Makefile workflows for updating LiteLLM, Hermes, and shared services independently.
  • Use case: Use it when you need to decide whether to route a request to Hermes, check budget pressure, or roll out only one AI component without restarting the whole stack.

Quick Start

Ask for an explanation of the agent mesh, the current routing rules, and the safest deploy command for the component you want to update.

Frequently Asked Questions about agent-mesh-mcp

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent runaway token spend when routing AI agent requests in a Kubernetes homelab?▼

To prevent runaway token spend during agent routing, use Prometheus and LiteLLM metrics to check budget pressure via PromQL before executing expensive operations. This cost-aware routing ensures economical model selection and tracks token spend across your homelab cluster.

What is the safest way to update a single AI component without restarting the whole K3s stack?▼

The safest way to update a single AI component without restarting the whole K3s stack is to use granular deployments with separated Ansible and Makefile workflows. This allows you to independently update LiteLLM, Hermes, or shared services.

How does agent communication routing work between OpenClaw and Hermes?▼

Agent communication routing between OpenClaw and Hermes works by delegating tasks across the cluster using an agent mesh architecture. This architecture coordinates task handoffs and granular deployment control through Kubernetes MCP services.

Do I need RBAC configured to run read-only or operator workflows in a K3s cluster?▼

Yes, you need RBAC configured to run safe, RBAC-controlled execution for read-only, operator, or admin workflows in a K3s cluster. This prevents accidental coupling and ensures secure access when coordinating agent communication.

Can I check my token budget before routing a request to Hermes?▼

Yes, you can check your token budget before routing a request to Hermes by applying Prometheus-driven spend checks. The system uses PromQL-based budget monitoring and LiteLLM metrics to verify budget pressure before deciding to route the request.

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