Ratatoskr FAQs

Question 1

What is Ratatoskr and what problem does it solve?

Accepted Answer

Ratatoskr is a no-code tool that automatically generates MCP (Model Context Protocol) servers from any API specification. It solves the boilerplate problem of wiring APIs for AI agents, optimizing responses, and enabling advanced data manipulation.

Question 2

How does Ratatoskr optimize API responses for AI agents?

Accepted Answer

It employs TOON (Token-Optimized Output Notation) compression, reducing API response tokens by 30-60% for LLMs. Additionally, an intelligent AI agent prunes large payloads, delivering only relevant data and improving LLM reasoning quality.

Question 3

What API specifications can Ratatoskr integrate with?

Accepted Answer

Ratatoskr offers zero-code integration with OpenAPI (REST), GraphQL endpoints, and Protobuf definitions. It introspects the schema automatically to expose API functionalities as MCP tools.

Question 4

Can Ratatoskr perform advanced data operations on API responses?

Accepted Answer

Yes, Ratatoskr allows SQL post-processing on API data using DuckDB. This means you can apply rankings, filters, and JOINs across endpoints, even if the underlying API does not natively support such operations.

Question 5

Which LLM providers does Ratatoskr support?

Accepted Answer

Ratatoskr is polyglot, providing first-class support for OpenAI, Anthropic (Claude), and various OpenAI-compatible models, including local LLM solutions like Ollama, LM Studio, and vLLM.

Ratatoskr

Ratatoskr

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主要功能

使用案例