Galileo

Galileo

Official
rungalileo

Connects to Galileo's platform for managing LLM evaluation datasets, monitoring application performance, and running experiments on language models.

Integrates with Galileo's evaluation and observability platform to enable dataset creation, prompt template management, experiment setup, log analysis, and step-by-step integration guides for monitoring LLM application performance.

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What it does

  • Create and manage evaluation datasets
  • Set up LLM experiments and A/B tests
  • Monitor model performance and observability metrics
  • Analyze application logs and traces
  • Manage prompt templates and versions
  • Access step-by-step integration guides

Best for

ML engineers evaluating LLM applicationsTeams running production language model servicesDevelopers optimizing prompt performanceOrganizations monitoring AI application quality
Full evaluation and observability platformStreamable HTTP transport

About Galileo

Galileo is an official MCP server published by rungalileo that provides AI assistants with tools and capabilities via the Model Context Protocol. Galileo: Integrate with Galileo to create datasets, manage prompt templates, run experiments, analyze logs, and monitor It is categorized under productivity, developer tools.

How to install

You can install Galileo in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.

License

Galileo is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

Galileo Docs

This repo is the source for Galileo's docs. We use Mintlify for building and publishing our docs.

Contributing

See our contributing guide for more details.

Dev container

This repo has a devcontainer configured so you can run in VS Code with the dev containers extension and Docker, or in a code space, and have an isolated environment with all the relevant tools installed.

This container installs the Mintlify CLI as well as Vale for spellchecking. It also has some recommended extensions. If you find any other extensions useful, please add them to the devcontainer.json file.

Build and view the docs

We use Mintlify for building and publishing our docs.

To build and run the doc locally:

  1. Install the Mintlify CLI:

    npm install -g mint
    
  2. Run the Mintlify CLI:

    mint dev
    

Check for broken links

Before pushing a change, check for broken links using:

mint broken-links

Check spellings

This repo is set up to use Vale to check spellings. To use it, first install Vale:

brew install vale

Then install MDX2VAST:

npm install -g mdx2vast

Then you can check spelling using:

vale . --glob='!{sdk-api/**/reference/**/*.*}'

This command ignores the generated SDK code.

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