A
licenseNot graded
qualityD
maintenanceNever start from zero. Persistent session intelligence for AI coding assistants.
45 npm
1
MIT
CONTINUITY
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@CONTINUITYsave session with handoff for my-project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CONTINUITY
Session state persistence for MCP systems: crash recovery, a decision registry, and context compression for long-running AI sessions.
The problem
A long working session with an AI assistant accumulates real state — decisions made, approaches tried and rejected, context that took real back-and-forth to establish. A crash, a context-window limit, or just closing the window loses all of it, and re-establishing that state by hand is expensive.
Related MCP server: handoff-mcp
What it does
CONTINUITY checkpoints session state as it develops, logs decisions explicitly rather than letting them live only in conversation history, and compresses context so a session can be resumed without replaying the entire prior conversation to get back to where it left off.
Part of a system
CONTINUITY is the session-recovery layer in a larger cognitive-infrastructure stack. See davidkirsch.me/builds for the rest.
This server cannot be deployed
Maintenance
ActivitySlowing
ResponsivenessNo issues
Related MCP Connectors
- AmberOAuthcom.ambermem
Long-term memory for AI assistants. Hybrid retrieval, query expansion, auto-topics.
- memoryOAuthcom.leapmemory
Long-term memory for AI assistants. Isolated per-user storage, recall across conversations.
Persistent memory for AI agents. Search, store, and recall across sessions.
Cross-tool persistent memory and context for AI assistants over MCP.
1
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