Local-first long-term memory for AI agents via a Markdown vault, offering MCP tools to query, ingest, lint, distill, and manage agent lessons and profile suggestions.
Structured, versioned context for AI agents. Context Nest organizes knowledge as markdown documents in a vault, with versioning, integrity verification, and a query language.
Open memory standard for AI agents. Local-first, MCP-native, lives in your Obsidian vault. Bi-temporal markdown, hybrid retrieval, reproducible benchmark.
Local-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.
Git-native long-term memory for AI agents: your markdown files are the source of truth, the search index is a disposable projection rebuilt from git, and every memory the agent writes is a reviewable git commit. Served over one OAuth-secured MCP endpoint with hybrid lexical+semantic recall and a gated, git-first commit_note write tool.