FieldFlow FAQs

Question 1

What is FieldFlow and what problem does it solve?

Accepted Answer

FieldFlow converts OpenAPI 3.0 specifications into dynamic, selectively filtered REST API tools. It solves the problem of excessive data retrieval by generating FastAPI routes that allow you to request only specific data fields from any API response, optimizing data transfer and processing.

Question 2

How does FieldFlow integrate with AI agents or LLMs?

Accepted Answer

It exposes generated OpenAPI tools via the Model Context Protocol (MCP), enabling AI agents and LLMs like Claude Desktop to discover and interact with APIs. Agents can then precisely request and receive only the data they need, enhancing their efficiency and context awareness.

Question 3

Can I filter specific fields from deeply nested API responses?

Accepted Answer

Yes, a core feature is its ability to accept an optional 'fields' list in requests. This allows you to 'slice' responses, including deeply nested data using a JSONPath-lite syntax (e.g., `moves[].move.name`), reducing data payload and improving relevance.

Question 4

What kind of API specifications and authentication methods does FieldFlow support?

Accepted Answer

FieldFlow works with any OpenAPI 3.0 compliant JSON or YAML specification. It supports secure API authentication via environment variables (Bearer, API Key, Basic) and automatically integrates with security schemes defined within your OpenAPI spec, ensuring credentials are handled securely.

Question 5

Does FieldFlow generate interactive API documentation?

Accepted Answer

Yes, when running in HTTP serve mode, FieldFlow leverages FastAPI to automatically publish interactive API documentation at `/docs` (e.g., `http://127.0.0.1:8000/docs`). This allows users to explore and invoke the generated tool endpoints interactively.

FieldFlow

FieldFlow

Key Features

Use Cases

Key Features

Use Cases