Advertise
MCP.so
Sign In
J

Judgmentlabs MCP Server

@suysoftware

Repository

Basic information

Category

Other

Transports

stdio

Author

suysoftware

Submitted by

Ufuk Yavuz

About Judgmentlabs MCP Server

A Model Context Protocol (MCP) server that provides seamless integration with the Judgment API for AI evaluation workflows. This server enables you to manage datasets, run evaluations, and track traces directly from your MCP-compatible environment.

#judgmentlabs#mcp-server#ai-evaluation

Judgmentlabs MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Judgmentlabs MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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.

Frequently asked questions

1

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.

2

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.

3

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`).

4

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.

5

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.

Comments

More Other MCP servers

Handl

Handl speaks the Model Context Protocol. Your whole billing operation — projects, invoices, clients, reports, approvals — as tools any AI assistant can call, inside your autonomy rules.

MCP Toolbox for Databases

googleapis

MCP Toolbox for Databases is an open source MCP server for databases.

15.9K

Volley.sh

Volley

A good sequence diagram can solve almost any communication problem in engineering. Volley lets your agent write them as plain text, with the real request and response payloads on every arrow. It checks its own syntax wi

Hindsight

vectorize-io

Hindsight: Agent Memory That Learns

50.4K

Figs, Relationship Expert

Figs O'Sullivan, LMFT

Couples therapist Figs O'Sullivan (LMFT, 17 years, endorsed by Sue Johnson, creator of EFT) inside your AI. Ask relationship questions answered from his clinical writing, name the pattern in a fight, get a three-step rep

Advertise