Skynet MCP Server

An MCP Server that acts as an agent and that can spawn more Agents, by using MCP.. MCP Inception!. That is what the skynet mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

The short version

A hierarchical network of AI agents using the Model Context Protocol (MCP). The AI Agents in this network can spawn new agents to have them do work, each agent also includes all the tools that the initiating agent has. The network of agents are capable of working through complex tasks, ranging from research, reporting, to coding.

Skynet-MCP is an advanced architecture that implements the Model Context Protocol (MCP) to create a hierarchical network of AI agents. Each Skynet-MCP instance acts as both an MCP server and MCP client, allowing it to provide tools to parent agents while also spawning and managing child agents.

• Dual-Mode Operation — Acts as both MCP server and client
• LLM Integration — Connect to OpenAI or Anthropic models for intelligent decision-making
• Tool Discovery — Automatically discover and use tools from connected MCP servers
• Hierarchical Agent Management — Create and manage child agents
• Configurable — Flexible configuration system supporting multiple environments
• FastMCP Integration — Built on the efficient FastMCP framework for robust MCP server implementations

The tools it exposes

The server publishes 8 tools. What each one is for:

• Parameters — - mcpConfig: MCP server configuration (available tools for the agent)
• llmConfig — LLM configuration (provider and model to use)
• prompt — Instructions for the agent task
• delayedExecution — Boolean indicating if the task should be run asynchronously
• Returns — Task status and result (if completed)
• Prerequisites — The Prerequisites tool exposed by this server
• Setup — 1. Clone the repository 2. Install dependencies: npm install
• Dockerfile — The Dockerfile tool exposed by this server

Getting it running

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

What it needs from you

Configuration is passed through the environment: SERVER_HOST, REDIS_URL, OPENAI_API_KEY, ANTHROPIC_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.

• Node.js (v20+) - npm - Docker and Docker Compose (optional, for containerized development) - API keys for OpenAI or Anthropic (for LLM-powered agents)

How it compares

Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Skynet's toolset — Parameters, llmConfig, prompt and 5 more — is a fair guide to whether it matches your workflow. It is maintained by ivo-toby; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against Skynet's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Things to watch

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
• Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.