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Data Access

Data access in the AI research context covers how AI tools connect to and query research data sources — from institutional databases like WRDS to public APIs like FRED and EDGAR.

Context & Background

Effective AI-assisted research requires the AI tool to access the same data sources researchers use. This can happen through:

  • API integration: Direct connections to data providers (WRDS Python API, FRED API)
  • MCP servers: Model Context Protocol connections that give AI tools database access
  • File-based access: Loading data files (CSV, Parquet) into the AI's working context
  • Database queries: AI-generated SQL or API calls to retrieve specific data

Practical Implications

  • Set up API credentials: Configure WRDS, FRED, and other API access in your environment
  • Use MCP for database access: Connect Claude Code to databases via MCP for seamless queries
  • Respect data agreements: Ensure AI tool use complies with data provider terms
  • Cache aggressively: Store downloaded data locally to reduce API calls and ensure reproducibility

Key Sources