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Persistent memory for coding agents across sessions
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "agent-memory" yet — see the docs or source repo.
Please save this project's naming conventions, folder structure, and tech stack choices to long-term memory, and keep following them in future code generation.
Stores project conventions in persistent Markdown memory.
Record my coding preferences: prefer TypeScript, functional style, and fewer classes; apply them by default in later responses.
Remembers user preferences and reduces repeated instructions.
Save the API error-handling approach we decided today, so we can continue from it when I come back next time.
Preserves key decisions so later sessions can continue smoothly.
Developers working on the same task over multiple sessions can keep requirements, agreements, and decisions remembered. This avoids re-explaining the project context later.
When a user wants the agent to consistently follow language, style, or implementation preferences, this tool can store them. Future outputs stay more consistent.
In collaborative coding, the agent can record agreed solutions and pending actions. That makes it easier to resume progress after interruptions or team changes.
It is a persistent memory tool for MCP coding agents, storing preferences, project context, and decisions across sessions. It saves this information in Markdown files.
According to the description, it stores memory in Markdown files.
It is for developers using MCP-powered coding agents, to help the agent remember project background, personal preferences, and prior decisions.
Give AI coding agents persistent semantic memory with embedding-based retrieval.
Give AI coding agents persistent memory across sessions for decisions and debugging context.
Give AI coding agents persistent local memory of your workflow and preferences.
Give AI coding agents searchable local project memory with safe structured updates.
Give AI coding agents persistent local shared memory across agents.
Store coding history, decisions, and fixes for AI agents in your repo.