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.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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:
-
Install the Mintlify CLI:
npm install -g mint -
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 69 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★69 reviews- ★★★★★Ganesh Mohane· Dec 28, 2024
Galileo reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Charlotte Martin· Dec 20, 2024
According to our notes, Galileo benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Arya Iyer· Dec 16, 2024
Galileo is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Liam Liu· Dec 8, 2024
We evaluated Galileo against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Arjun Martin· Dec 4, 2024
Useful MCP listing: Galileo is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Chen Kim· Nov 27, 2024
Galileo has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Layla Iyer· Nov 23, 2024
Strong directory entry: Galileo surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Sakshi Patil· Nov 19, 2024
I recommend Galileo for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Chen Thomas· Nov 15, 2024
Galileo is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Ama Okafor· Nov 11, 2024
Galileo is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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