🦉 Trustwise MCP Server

The Trustwise MCP Server is a Model Context Protocol (MCP) server that provides a suite of advanced evaluation tools for AI safety, alignment, and performance. It enables developers and AI tools to programmatically assess the quality, safety, and cost of LLM outputs using Trustwise's industry-leading metrics.

💡 Use Cases

• Evaluating the safety and reliability of LLM responses.
• Measuring alignment, clarity, and helpfulness of AI-generated content.
• Estimating the carbon footprint and cost of model inference.
• Integrating robust evaluation into AI pipelines, agents, or orchestration frameworks.

🛠️ Prerequisites

• A Trustwise API Key (get one here)
• Docker; Follow the install instructions

📦 Installation & Running

Claude Desktop

To connect the Trustwise MCP Server to Claude Desktop, add the following configuration to your Claude Desktop settings:

{
  "mcpServers": {
    "trustwise": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "TW_API_KEY",
        "ghcr.io/trustwiseai/trustwise-mcp-server:latest"
      ],
      "env": {
        "TW_API_KEY": "<YOUR_TRUSTWISE_API_KEY>"
      }
    }
  }
}

To point to a specific Trustwise Instance - under env, also set the following optional environment variable:

TW_BASE_URL: "<YOUR_TRUSTWISE_INSTANCE_URL>"

e.g "TW_BASE_URL": "https://api.yourdomain.ai"

Cursor

To connect the Trustwise MCP Server to cursor, add the following configuration to your cursor settings:

{
  "mcpServers": {
    "trustwise": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "TW_API_KEY",
        "-e",
        "TW_BASE_URL",
        "ghcr.io/trustwiseai/trustwise-mcp-server:latest"
      ],
      "env": {
        "TW_API_KEY": "<YOUR_TRUSTWISE_API_KEY>"
      }
    }
  }
}

Replace <YOUR_TRUSTWISE_API_KEY> with your actual Trustwise API key.

🧰 Tools

The Trustwise MCP Server exposes the following tools (metrics). Each tool can be called with the specified arguments to evaluate a model response.

🛡️ Trustwise Metrics

Tool Name	Description
faithfulness_metric	Evaluate the faithfulness of a response to its context
answer_relevancy_metric	Evaluate relevancy of a response to the query
context_relevancy_metric	Evaluate relevancy of context to the query
pii_metric	Detect PII in a response
prompt_injection_metric	Detect prompt injection risk
summarization_metric	Evaluate summarization quality
clarity_metric	Evaluate clarity of a response
formality_metric	Evaluate formality of a response
helpfulness_metric	Evaluate helpfulness of a response
sensitivity_metric	Evaluate sensitivity of a response
simplicity_metric	Evaluate simplicity of a response
tone_metric	Evaluate tone of a response
toxicity_metric	Evaluate toxicity of a response
refusal_metric	Detect refusal to answer or comply with the query
completion_metric	Evaluate completion of the query’s instruction
adherence_metric	Evaluate adherence to a given policy or instruction
stability_metric	Evaluate stability (consistency) of multiple responses
carbon_metric	Estimate carbon footprint of a response
cost_metric	Estimate cost of a response

For more examples and advanced usage, see the official Trustwise SDK.

📄 License

This project is licensed under the terms of the MIT open source license. See LICENSE for details.

🔒 Security

• Do not commit secrets or API keys.
• This repository is public; review all code and documentation for sensitive information before pushing.

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