The **Trustwise MCP Server** is a [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) server that provides a suite of
Trustwise mcp server connects Trustwise to AI assistants that speak the Model Context Protocol. 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.
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.
Once connected, the assistant can call this tool directly:
Cursor — To connect the Trustwise MCP Server to cursor, add the following configuration to your cursor settings:Setup follows the standard MCP pattern: clone or install the server, then register it in your client's configuration file and restart the client. The configuration snippets on this page cover Claude Desktop, Claude Code and Cursor.
Before the server will start you need to supply 4 environment variables: TW_API_KEY, TW_BASE_URL, YOUR_TRUSTWISE_API_KEY, YOUR_TRUSTWISE_INSTANCE_URL. Keep credentials in your client's env block or a secrets manager rather than committing them.
AI-service servers chain other models into your assistant, turning a single chat into a small production pipeline. Trustwise sits in that group, and the shape of its toolset — Cursor — tells you what it is really for. Worth comparing against the other ai services servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.
| Tool | What it does |
|---|---|
| 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",
"ghcr.io/trustwiseai/trustwise-mcp-server:latest"
],
"env": {
"TW_API_KEY": "<YOUR_TRUSTWISE_API_KEY>"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| TW_API_KEY | Credential the server authenticates with. | Yes |
| TW_BASE_URL | Endpoint or connection string the server talks to. | Yes |
| YOUR_TRUSTWISE_API_KEY | Credential the server authenticates with. | Yes |
| YOUR_TRUSTWISE_INSTANCE_URL | Endpoint or connection string the server talks to. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.