Shared project memory for AI coding agents

What is shared project memory?

Shared project memory is a durable record of what a project currently understands. It can explain why a design was chosen, which approach was rejected, what evidence supports a decision, and what still needs an answer.

In Klypix, the record lives with the project. A supported agent can retrieve relevant context through the Model Context Protocol (MCP), then record new findings in the same brain. An explicit correction can supersede an older decision while preserving its history.

The Windows workspace lets a person inspect and edit that understanding beside files, notes and evidence. The open-source klypix-mcp engine connects coding tools to the brain.

How does a coding-tool handoff work?

Consider a hypothetical authentication change. A Claude Code session records that refresh tokens must stay on the server and links the decision to its evidence. Later, a Codex session starts work on sign-in in the same project.

1. Declare the task. The new session calls brain_sync with the project path, its intent and the exact files it expects to touch.
2. Retrieve the reasoning. Task-relevant context comes back. The session can ask brain_ask for the earlier authentication decision and its correction history.
3. Check a proposed change. brain_challenge can surface conflicting prior decisions or standing rules. An empty result does not prove the proposal is correct.
4. Record what changed. The session captures a useful finding or explicit correction with brain_note, then marks its task complete with brain_sync.

The next session receives the understanding that was captured. It still needs to inspect the current code and verify that the evidence applies.

Which tools can use the same brain?

Integration depth varies by host. This is the distinction to check when choosing how to connect a project:

Use the current setup documentation for the host you run. A configured connection and a successful task-context retrieval are useful checks before relying on a handoff.

When is a rules file enough?

A short AGENTS.md or CLAUDE.md file can be enough for stable conventions in a small project. It is easy to review and version in Git.

Klypix becomes useful when the record includes changing decisions, rejected approaches, supporting evidence and open questions across sessions. Rules can tell a supported agent to consult the brain; the brain supplies task-relevant context and preserves explicit corrections. Git continues to version the code and the brain file.

What are the limits?

• It starts with what you capture. A new brain does not reconstruct the project’s missing history.
• Live coordination is local. Default session presence and exact-file overlap warnings apply to connected sessions for the same OS user on the same machine. Warnings are advisory and rely on declared file paths.
• Teammates share durable context through Git. Committing and pulling brain.klypix carries the record between computers. It does not make their live sessions visible to one another.
• You choose and run the agents. Klypix does not launch, route or supervise them.
• Check the privacy boundary. The brain file is local, but an AI provider can receive context supplied to its agent. See the privacy policy before using sensitive project information.

Try it on one project

Follow the klypix-mcp installation instructions for your coding host. Start in a project you can use for a small trial:

npx klypix-mcp install

Capture one real decision and the reason behind it. Start a new supported session, ask what was decided, and inspect the returned evidence. Then record an explicit correction and repeat the question. This checks the handoff against your own workflow.

For the visual workspace, download Klypix for Windows. For current availability and plan details, see pricing.