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Galileo▌

by rungalileo

Galileo: Integrate with Galileo to create datasets, manage prompt templates, run experiments, analyze logs, and monitor

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.

github stars

★ 5

GitHubWebsite
Full evaluation and observability platformStreamable HTTP transport

best for

  • / ML engineers evaluating LLM applications
  • / Teams running production language model services
  • / Developers optimizing prompt performance
  • / Organizations monitoring AI application quality

capabilities

  • / 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

what it does

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

about

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

MIT

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

readme

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.

FAQ

What is the Galileo MCP server?
Galileo is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Galileo?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.5★★★★★10 reviews
  • ★★★★★Shikha Mishra· Oct 10, 2024

    Galileo is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • ★★★★★Piyush G· Sep 9, 2024

    We evaluated Galileo against two servers with overlapping tools; this profile had the clearer scope statement.

  • ★★★★★Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Galileo is the kind of server we cite when onboarding engineers to host + tool permissions.

  • ★★★★★Sakshi Patil· Jul 7, 2024

    Galileo reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • ★★★★★Ganesh Mohane· Jun 6, 2024

    I recommend Galileo for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • ★★★★★Oshnikdeep· May 5, 2024

    Strong directory entry: Galileo surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • ★★★★★Dhruvi Jain· Apr 4, 2024

    Galileo has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★Rahul Santra· Mar 3, 2024

    According to our notes, Galileo benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • ★★★★★Pratham Ware· Feb 2, 2024

    We wired Galileo into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Yash Thakker· Jan 1, 2024

    Galileo is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.