MCP-Memoryis a Model Context Protocol (MCP) server that equips AI agents (such as Claude Desktop, Cursor, Antigravity, Windsurf, or Codex) with persistent, long-term memory capabilities.
Memory records are formatted using theOpen Knowledge Format (OKF v0.2)standard and indexed with a localSQLiteinstance (supporting FTS5 full-text search) for fast key-value lookups, tag filtering, and content search.
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The server exposes four primary MCP tools to interacting agents:
Stores or updates a memory record in OKF v0.2 format.
Retrieves a specific memory by its key and namespace.
Finds memories matching keywords, tags, or namespace filters.
AGENT DIRECTIVE (Session Start):Retrieves the last recorded session checkpoint (system/last_memory) so the AI agent immediately knows where work was left off when opening a project or starting a session.
AGENT DIRECTIVE (Milestones & Progress):Updates the canonical session checkpoint (system/last_memory) whenever completing a milestone, making key changes, or pausing work.
Every stored memory strictly adheres to the OKF v0.2 specification (SPEC.md&OKF_RULES.md):
Runsetup.pyto auto-detect and registermcp-memorywith your AI tools:
Note:Oncesetup.pyfinishes configuring your tools, your AI client will launchmcp-memoryautomatically in the background whenever needed. You do not need to manually start or keep a server process running in your terminal.