Agentkeep FAQs

Question 1

Is Agentkeep suitable for coding assistants?

Accepted Answer

Absolutely. It's specifically designed with a fixed schema and a narrow tool surface, making it ideal for coding assistants to store and retrieve high-signal project memory efficiently, reducing prompt and response sizes.

Question 2

What kind of information can Agentkeep store?

Accepted Answer

Agentkeep stores crucial project memory including agent identities, their current thoughts, process-level changes, known issues, process recommendations, and agent contributions. Each record type follows a predictable, lifecycle-oriented structure.

Question 3

Can I perform advanced database operations or migrations?

Accepted Answer

Yes. While Agentkeep offers a focused API for common operations, it also provides an `execute_sql` tool. This escape hatch allows you to run raw SQL queries against the underlying SQLite database for debugging, migrations, or other advanced interactions.

Question 4

What is Agentkeep and what problem does it solve?

Accepted Answer

Agentkeep is a Rust-based Model Context Protocol (MCP) stdio server that provides a dedicated, project-local SQLite database for managing AI agent activity and high-signal memory. It solves the challenge of storing and retrieving specific project context for coding assistants with minimal token overhead.

Question 5

How does Agentkeep manage its database?

Accepted Answer

Agentkeep automatically initializes and manages a project-local SQLite database, defaulting to `.agentkeep.sqlite` in your working directory. This ensures each project has its own isolated memory store without complex configuration.

Agentkeep

Agentkeep

主要功能

使用案例

主要功能

使用案例