baselight-mcp
Connects to the Baselight MCP (Model Context Protocol)
Setup & Installation
Install command
clawhub install pjsousa79/baselight-mcpIf the CLI is not installed:
Install command
npx clawhub@latest install pjsousa79/baselight-mcpOr install with OpenClaw CLI:
Install command
openclaw skills install pjsousa79/baselight-mcpor paste the repo link into your assistant's chat
Install command
https://github.com/openclaw/skills/tree/main/skills/pjsousa79/baselight-mcpWhat This Skill Does
Baselight MCP connects AI tools and IDEs to 50+ structured dataset sources via the Model Context Protocol. Users discover datasets, inspect schemas, and run live SQL queries against sources like Kaggle, World Bank, FRED, SEC filings, and crypto markets without leaving their AI client.
Gives AI tools direct SQL access to 50+ curated data sources without manual downloads or separate API integrations for each provider.
When to Use It
- Querying FRED for US unemployment trends over the past decade
- Pulling SEC filings to compare a company's annual revenue
- Analyzing NFLverse stats for fantasy football lineup decisions
- Fetching World Bank GDP data for a country comparison report
- Running SQL on Polymarket data to track prediction market outcomes
View original SKILL.md file
# Baselight MCP Use Baselight via MCP to browse, discover, and query Baselight datasets directly from your AI tool or IDE. MCP Server URL: https://api.baselight.app/mcp ## When to Use This Skill - User wants datasets for a topic - User wants structured tables - User wants SQL analysis - User wants verifiable results ## Quick Start Connect using OAuth or API key depending on client. ### OAuth Clients - ChatGPT connectors - Claude Web/Desktop ### API Key Clients - VS Code - Gemini CLI - LibreChat ------------------------------------------------------------------------ ## Workflow 1. Understand question 2. Discover datasets 3. Inspect schema 4. Query data 5. Return results + SQL ------------------------------------------------------------------------ ## Query Format Tables use: @username.dataset.table Example: SELECT \* FROM @user.soccer.matches LIMIT 10; ------------------------------------------------------------------------ ## Best Practices - Discover first - Inspect schema - Query iteratively - Include SQL - Explain assumptions ------------------------------------------------------------------------ ## Limitations - Requires Baselight account or API key - Query limits may apply - Dataset freshness varies ------------------------------------------------------------------------ ## Troubleshooting Connection fails: - Verify MCP URL - Reauthenticate or regenerate key Unauthorized: - Invalid key or expired OAuth Slow query: - Reduce scope - Add LIMIT ------------------------------------------------------------------------ ## Support Docs: https://baselight.ai/docs/connecting-to-the-baselight-mcp-server/ App: https://baselight.app
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Querying FRED for US unemployment trends over the past decade
- 1Querying FRED for US unemployment trends over the past decade
- 2Pulling SEC filings to compare a company's annual revenue
- 3Analyzing NFLverse stats for fantasy football lineup decisions
- 4Fetching World Bank GDP data for a country comparison report
- 5Running SQL on Polymarket data to track prediction market outcomes
Connects to the Baselight MCP (Model Context Protocol)
Security Audits
These signals reflect official OpenClaw status values. A Suspicious status means the skill should be used with extra caution.