Memory for your agent.

Stop re-explaining your projects. Persistent context across every session.

The fragmented approach

  • Chat history → memory
  • Notion → project state
  • Jira → task tracking
  • Confluence → lessons
  • grep → search
or

One unified memory layer

  • start → load full context
  • checkpoint → persist progress
  • lesson → capture knowledge
  • search → recall solutions

One protocol. Persistent intelligence.

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How it works

Synthesis MCP gives your AI persistent, structured memory. It centralizes project state, decisions, work logs, and lessons in a secure Global Hub that any AI tool can access through the Model Context Protocol.

Your source code stays clean. All memory lives outside your repository.

How Synthesis works diagram
The 4-tool API

synthesis_start

Load project context at session start. Returns current state, next steps, blockers, and relevant lessons.

synthesis_checkpoint

Save progress after meaningful work. Updates CONTEXT.md, marks steps complete, creates work logs.

synthesis_lesson

Capture reusable knowledge. Record bug fixes or useful techniques. Surfaced automatically in future sessions.

synthesis_search

Search past lessons when stuck. Find solutions to problems you've solved before, across all projects.

Secure by design

Knowledge, not code

We never store your source code or project files. Only the context you create - summaries, decisions, lessons. Your codebase stays on your machine.

Your keys, your access

API keys are SHA-256 hashed before storage. We never see your plaintext keys. Revoke access instantly from your dashboard.

Isolated per user

Row-level security ensures your knowledge is only accessible with your authenticated API key. No cross-user data access.

Open protocol

Built on Model Context Protocol. Inspect every request your AI makes. Self-host if you want complete control.

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