# baselight MCP server

Query Baselight's public catalog of 70,000+ datasets — finance, demographics, sports, and more.

## Links
- Registry page: https://www.getdrio.com/mcp/ai-baselight-baselight
- Website: https://baselight.ai

## Install
- Endpoint: https://api.baselight.app/mcp
- Auth: Auth required by registry metadata

## Setup notes
- Remote header: x-api-key (required; secret)
- The upstream registry signals required auth or secrets.
- Remote endpoint: https://api.baselight.app/mcp
- Header: x-api-key

## Tools
- baselight_ping (Ping Test) - Simple ping test to verify MCP server is responding Endpoint: https://api.baselight.app/mcp
- baselight_search_catalog (search_catalog) - Search the catalog for datasets using a text query and filters. Datasets in Baselight have the following format: @username.dataset. Datasets can be public or private — you can search and use all public datasets as well as the user's private datasets. This is typically the first step in the discovery workflow. Endpoint: https://api.baselight.app/mcp
- baselight_search_tables (search_tables) - Search for tables using a text query and filters. Tables in Baselight have the following format: @username.dataset.table. Tables are grouped into datasets which can be public or private — you can search and use all public datasets as well as the user's private datasets. Search for tables directly when you are unable to find relevant datasets. Endpoint: https://api.baselight.app/mcp
- baselight_get_dataset_metadata (get_dataset_metadata) - Retrieve detailed schema and metadata for a specific dataset using Baselight format @username.dataset. Use this after discovering datasets to understand their structure before querying. Tables within datasets follow the format @username.dataset.table (always double-quoted identifiers in SQL). Endpoint: https://api.baselight.app/mcp
- baselight_get_dataset_tables (get_dataset_tables) - Retrieve a paginated list of tables from a specific dataset using Baselight format @username.dataset. Use this tool to browse datasets with many tables or to search for specific tables within a dataset. Each page returns up to 100 tables with metadata. Endpoint: https://api.baselight.app/mcp
- baselight_get_table_metadata (get_table_metadata) - Retrieve detailed schema and metadata for a specific table using Baselight format @username.dataset.table. Use this to understand table structure, column types, and constraints before writing SQL queries. Tables must be referenced in SQL with double quotes. Endpoint: https://api.baselight.app/mcp
- baselight_get_user (get_user) - Retrieve detailed information about a Baselight user including their profile bio, website, and public datasets. Use this to understand who owns datasets you're interested in. Endpoint: https://api.baselight.app/mcp
- baselight_sdk_query_execute (sdk_query_execute) - Execute a SQL query on Baselight and wait for results (up to 1 minute). The query executes and returns the first 100 rows upon completion, or info about a pending query that needs more time. Use DuckDB syntax only, table format "@username.dataset.table" (double-quoted), SELECT queries only (no DDL/DML), no semicolon terminators, use LIMIT not TOP. If query is still PENDING, use `sdk-get-results` to continue polling. If totalResults > returned rows, use `sdk-get-results` with offset to paginate. Endpoint: https://api.baselight.app/mcp
- baselight_sdk_get_results (sdk_get_results) - Retrieve results from a previously executed SDK job using the resultId from `sdk-query-execute`. If the query is complete, returns results immediately. If still pending, polls for up to 1 more minute. Use this after `sdk-query-execute` returns PENDING status. Endpoint: https://api.baselight.app/mcp

## Resources
Not captured

## Prompts
- baselight-initial-prompt - A prompt to initialize interaction with the Baselight catalog and understand its capabilities

## Metadata
- Owner: ai.baselight
- Version: 1.0.0
- Runtime: Streamable Http
- Transports: HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: Apr 30, 2026
- Source: https://registry.modelcontextprotocol.io