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Provide Git-backed Markdown memory and clean search for AI agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Engram" yet — see the docs or source repo.
Search the Engram memory for "API authentication flow" and return only current Markdown notes that are neither archived nor superseded.
A list or summary of current notes about API authentication flow, with archived and superseded content automatically excluded.
Save the following to Engram: deployment steps, rollback commands, and precautions for Project Alpha, organized in Markdown.
A structured Markdown memory entry is created and saved for later versioning and search.
Update the old "onboarding checklist" note to the latest process, mark the old content as superseded, and ensure future searches show the new version first.
The updated note is saved, and superseded older content is hidden from search results.
Developers can store an agent's accumulated knowledge as Git-managed Markdown notes. This preserves change history and makes the memory easy for agents to reuse.
When a knowledge base contains old, archived, and updated notes, users can focus searches on currently valid content. This reduces the chance that an agent relies on outdated information.
It is an MCP tool that provides Git-backed Markdown memory storage for AI agents. It also supports search and hides notes that are archived or superseded.
Based on the provided description, its search hides superseded and archived notes. That means results are biased toward content that is still current.
The provided material does not include installation steps, runtime requirements, or key requirements. See the source repository for details.
Query and store private local memories with temporal reasoning and citations.
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Provide fully offline, encrypted vector memory storage for AI agents.
Provide AI assistants with persistent project memory to avoid repeating context.
Provide tamper-evident audit and embedded memory storage for AI agents.