Kleio

Use case

Your AI agent builds up solid reasoning.
Then the session ends.

The biggest pain point is starting fresh every session. Kleio captures decisions inline via MCP, so context compounds instead of resetting.

The cost of context loss

  • Every new session starts from zero. The agent has no idea what you decided yesterday.
  • Reasoning context accumulates during development but vanishes the moment anything interrupts the session.
  • Six months of Cursor and nobody was thinking about structure — duplicate functions, three different ways to handle the same thing.
  • Half the time is spent re-feeding context instead of building.
  • AI-generated code drifts from architecture because agents can't remember prior decisions.

How Kleio helps

Inline MCP capture

Decisions are captured directly in your editor as you work. No separate tool, no context switch. The MCP server hooks into Cursor, Claude Code, and VS Code.

Cross-session memory via kleio_ask

Ask "what did we decide about auth last week?" and get answers grounded in your actual decision history — not a hallucinated summary.

Checkpoints that survive rebases

Mark implementation slices with validation status and context. Unlike commits, checkpoints preserve meaning through squash merges and rebases.

Automatic GitHub signal integration

PRs, reviews, CI results, and commits are captured as signals and linked to your decisions, building a provenance trail automatically.

See it in action

An agent plans a migration. Kleio captures every signal along the way.

Agent Plan

Task: Migrate auth from Firebase to Clerk

  • 1.Scaffold Clerk provider and session hooks
  • 2.Replace Firebase login/signup flows
  • 3.Update API middleware for Clerk JWT validation

Press Build to run the capture demo.

Your AI agents already make decisions. Kleio makes sure they're remembered. Try it free →

Ready to try Kleio?

Start free, connect your workspace, and stop losing the \u201cwhy.\u201d