agent-as-model MCP server

agent-as-model

A true MCP server where the agent is the model and the API key.

mcp-name: io.github.fernandogarzaaa/agent-as-model

Install

uvx agent-as-model

One-click install for VS Code:

The deep link carries the server's real install config ({"name":"agent-as-model","command":"uvx","args":["agent-as-model"]}) URL-encoded in the vscode:mcp/install? handler, the format from the official VS Code MCP developer guide.

Host scope: sampling-capable hosts only

This server does its work through MCP sampling, so one-click install and the guides below are scoped to sampling-capable hosts: VS Code, Goose, fast-agent, and opencode. Claude Code and Cursor are excluded until they implement sampling. The manual Claude Code instructions further down stay for anyone who wants to experiment anyway.

Goose

Add to ~/.config/goose/config.yaml (or use goose configure and pick Add Extension, Command-line Extension):

extensions:
  agent-as-model:
    enabled: true
    type: stdio
    name: agent-as-model
    cmd: uvx
    args: ["agent-as-model"]
    timeout: 300

fast-agent

Add under mcp.servers in fastagent.config.yaml, then include agent-as-model in your agent's servers=[...] list:

mcp:
  servers:
    agent-as-model:
      transport: "stdio"
      command: "uvx"
      args: ["agent-as-model"]

opencode

opencode mcp add agent-as-model -- uvx agent-as-model

Or in opencode.json (project root or ~/.config/opencode/opencode.json):

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "agent-as-model": {
      "type": "local",
      "command": ["uvx", "agent-as-model"]
    }
  }
}

Manual

Claude Code (kept as manual instructions; excluded from one-click until sampling is implemented):

claude mcp add agent-as-model -- uvx agent-as-model

Any client that takes MCP JSON, paste this:

{
  "mcpServers": {
    "agent-as-model": {
      "command": "uvx",
      "args": ["agent-as-model"]
    }
  }
}

Requires Python 3.10+ and a host that declares the MCP sampling capability. No API keys, ever.

From a local checkout: python -m agentasmodel. From the repo without installing: uvx --from git+https://github.com/fernandogarzaaa/agent-as-model agent-as-model.

The idea

AI products usually demand a model API key before they do anything useful. This server flips that around. The tools speak the request shapes products already use, and the intelligence comes from the agent on the other end of the MCP connection. The agent is the model. The agent is the key.

Tools

chatcomplete** — OpenAI chat-completions-shaped request, completion text back.

{
  "messages": [
    {"role": "system", "content": "You are terse."},
    {"role": "user", "content": "Explain MCP sampling."}
  ],
  "model": "agent-default",
  "temperature": 0.7,
  "max_tokens": 500
}

messagescreate** — Anthropic messages-shaped request, completion text back. system accepts a string or a list of text blocks. Message content accepts a string or a list of text blocks.

Shortened. The full README is on GitHub.