CI-1T Prediction Stability Engine MCP Server

CI-1T MCP Server

Version: 1.7.0
Last Updated: February 27, 2026
License: Proprietary

MCP (Model Context Protocol) server for the CI-1T prediction stability engine. Lets AI agents — Claude Desktop, Cursor, Windsurf, VS Code Copilot, and any MCP-compatible client — evaluate model stability, manage fleet sessions, and control API keys directly.

One credential. One env var. That's it.

Tools (20) + Resources (1)

Onboarding

New users get guided setup automatically. If no API key is configured:

• Startup log prints a hint: "Create a free account at collapseindex.org — 1,000 free credits on signup"
• onboarding tool returns a full welcome guide with account status, setup steps, config examples, available tools, and pricing
• Auth-guarded tools return a friendly error with specific setup instructions instead of a raw 401
• Utility tools (interpret_scores, convert_scores, generate_config) always work — no auth, no credits

Every new account gets 1,000 free credits (no credit card required), enough for 1,000 evaluation episodes.

Setup

Environment Variables

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "ci1t": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "collapseindex/ci1t-mcp"],
      "env": {
        "CI1T_API_KEY": "ci_your_key_here"
      }
    }
  }
}

Cursor / Windsurf

Add to .cursor/mcp.json or equivalent:

{
  "mcpServers": {
    "ci1t": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "collapseindex/ci1t-mcp"],
      "env": {
        "CI1T_API_KEY": "ci_your_key_here"
      }
    }
  }
}

VS Code (GitHub Copilot)

Add to .vscode/mcp.json:

{
  "servers": {
    "ci1t": {
      "type": "stdio",
      "command": "docker",
      "args": ["run", "-i", "--rm", "collapseindex/ci1t-mcp"],
      "env": {
        "CI1T_API_KEY": "ci_your_key_here"
      }
    }
  }
}

Run from source (no Docker)

git clone https://github.com/collapseindex/ci1t-mcp.git
cd ci1t-mcp
npm install
npm run build

# Set env var and run
CI1T_API_KEY=ci_xxx node dist/index.js

Build Docker Image

docker build -t collapseindex/ci1t-mcp .

Example Usage

Once connected, an AI agent can:

"Evaluate these prediction scores: 45000, 32000, 51000, 48000, 29000, 55000"

The agent calls evaluate with scores: [45000, 32000, 51000, 48000, 29000, 55000] and gets back stability metrics per episode, including credits used and remaining.

"Create a fleet session with 4 nodes named GPT-4, Claude, Gemini, Llama"

"List my API keys"

"Probe this prompt for stability: What is the capital of France?"

"Probe my local Ollama llama3 model with: What is the meaning of life?"

The agent calls probe in BYOM mode — sends the prompt 3x to http://localhost:11434/v1 an