Judgmentlabs Mcp Server

What is Judgmentlabs Mcp Server?

Judgmentlabs Mcp Server is a Model Context Protocol (MCP) server that integrates with the Judgment API to manage datasets, run evaluations, and track traces from MCP-compatible environments like Claude Desktop. It is built for AI evaluation workflows.

How to use Judgmentlabs Mcp Server?

Install via Claude Desktop’s DXT extension system (download the .dxt file from releases, then install through Settings → Extensions) or build from source. Configure your JUDGMENT_API_KEY and JUDGMENT_ORG_ID in the extension settings. After enabling and restarting Claude Desktop, use the provided tools (e.g., push_dataset, run_evaluation) through natural language prompts.

Key features of Judgmentlabs Mcp Server

• One-click DXT installation with no Python dependencies.
• Create, update, and retrieve datasets with flexible data handling.
• Create and delete projects; auto-creates projects when pushing datasets.
• Run evaluations and fetch detailed results.
• Create, fetch, and delete individual traces.
• Cross‑platform support (Windows, macOS, Linux).

Use cases of Judgmentlabs Mcp Server

• Push labeled datasets to Judgment API for model evaluation.
• Execute evaluation runs and retrieve results for analysis.
• Monitor AI agent behavior by managing traces in real time.
• Clean up projects and associated data when no longer needed.
• Automate dataset versioning with append or overwrite modes.

FAQ from Judgmentlabs Mcp Server

What are the prerequisites for running Judgmentlabs Mcp Server?

You need Claude Desktop (latest version with DXT support), a JudgmentLabs account with API access, and optionally Python 3.8+ for manual installation.

How do I install Judgmentlabs Mcp Server?

The recommended method is downloading the judgmentlabs-mcp-server.dxt file from the releases page and installing it via Claude Desktop’s Settings → Extensions. Advanced users can build the package from source using the DXT CLI.

What tools does Judgmentlabs Mcp Server provide?

It offers tools for dataset operations (push_dataset, get_dataset, delete_dataset), project management (create_project, delete_project), evaluation (run_evaluation, get_evaluation_results), and trace management (get_trace, delete_trace).

How are API credentials handled securely?

API keys are stored in Claude Desktop’s extension configuration, not in plain text files. Each extension runs in its own secure environment, and all data is transmitted securely to the Judgment API.

Are there any performance or size limits?

The server supports datasets with thousands of examples, handles batch operations efficiently, and respects API rate limits with proper error handling.