Sayou FAQs

Question 1

What integration options are available for Sayou?

Accepted Answer

Sayou provides flexible integration points, including a Python library, a CLI, an optional REST API, and an MCP (Multi-Agent Communication Protocol) server. It also has specific plugins for environments like Claude Code, Cursor, and Windsurf, making it accessible to various AI development setups.

Question 2

Can Sayou be used for structured and unstructured data?

Accepted Answer

Yes, Sayou is designed for both. It stores data in files with YAML frontmatter for structured metadata and Markdown content for rich, unstructured text. Additionally, it includes a key-value store for configurations or cached data, making it versatile for diverse agentic data needs.

Question 3

How does Sayou ensure knowledge persistence and context accumulation for AI agents?

Accepted Answer

Sayou achieves this through versioned files with YAML frontmatter and Markdown content. Every change is an append-only version, creating a full audit trail and enabling 'time-travel' reads, ensuring knowledge compounds over time rather than being forgotten.

Question 4

What are the key features for retrieving information from Sayou?

Accepted Answer

Sayou offers token-budget-aware content retrieval, which returns summaries with section pointers for large documents to fit within an agent's context window. It also includes comprehensive search capabilities (full-text, frontmatter filters, semantic search) and specific tools for history, glob, and grep operations.

Question 5

What is Sayou and its primary purpose?

Accepted Answer

Sayou is an open-source, file-system inspired context store designed for AI agents. Its primary purpose is to provide persistent memory, enabling agents to accumulate knowledge, retain context across sessions, and perform nuanced information retrieval, replacing traditional databases for AI workflows.

Sayou

Sayou

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