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Tools are the bridge between your AI agent and the outside world. This guide covers patterns for integrating external APIs, databases, and services as tools.

Tool Architecture

Basic Tool Handler

Tool Registry Pattern

For larger applications, use a registry:

Integrating REST APIs

HTTP Client Tool

GitHub API Integration

Integrating Databases

PostgreSQL Integration

Rate Limiting

Protect external services from abuse:

Error Handling

Return structured errors for better LLM understanding:

Context-Aware Tools

Pass execution context to tools:

Tool Documentation for LLMs

Generate tool documentation for LLM prompts:

Testing Tools

Best Practices

  1. Validate all inputs - Never trust data from the sandbox
  2. Use typed parameters - Define clear parameter schemas
  3. Return structured data - JSON-serializable results only
  4. Limit data size - Cap array lengths and string sizes
  5. Log all calls - Audit trail for debugging
  6. Handle errors gracefully - Return structured error objects
  7. Rate limit external calls - Protect APIs from abuse
  8. Timeout long operations - Don’t block indefinitely