mcp-memory: SQLite FTS5 + Google's OKF for Fast Agent Memory
Looking for a way to give your AI coding agent persistent memory without bolting on a heavy vector database? mcp-memory is an open-source MCP server that stores agent memory as Google's OKF v0.2 Markdown files, indexes everything locally with SQLite FTS5, and exposes four clean MCP tools. It's designed to drop into Claude Desktop, Cursor, Antigravity, Windsurf, or Codex with a zero-boilerplate setup wizard.
What it does
mcp-memory maintains a dual-layer architecture:
- Human-browseable OKF directory: Every memory is dumped as a raw
.mdfile insidememory/, with a rootindex.md(versioned withokf_version: "0.2") and alog.mdfor update history. - SQLite FTS5 index: Full-text search and triggers keep key lookups under 20ms and keyword searches instant.
Memories are stored as OKF v0.2 Markdown documents with YAML frontmatter (type, key, namespace, tags, generated, sources, verified, status, stale_after).
MCP tools
The server exposes four primary tools:
memory_store– Stores or updates a record. Requireskey,content, andproject_root. Optional:tags,namespace(defaultdefault),concept_type,title,description,resource,status,stale_after,sources,verified,generated_by.memory_retrieve– Gets a specific memory bykeyandnamespace.memory_search– Finds memories byquery,tags, ornamespace. Supportslimit(default 10).memory_get_last– Retrieves the last session checkpoint (system/last_memory) so the agent knows where work left off.
Namespace isolation and setup
Memories are scoped by namespace (e.g., user/preferences, project/architecture), keeping contexts separate. Setup is a single command:
python3 setup.py
This auto-configures installed MCP tools (Antigravity, Claude, Cursor, Windsurf, Codex). The server also supports a project_root parameter for every tool, so you can keep per-project memory stores.
Who it's for
Developers using AI coding agents (Claude, Cursor, etc.) who want persistent, searchable memory that stays in plain-text Markdown and doesn't require a vector DB or external service.
📖 Read the full source: HN AI Agents
👀 See Also

Skir: A Modern Alternative to Protocol Buffers for Type-Safe Data Exchange
Skir is a declarative language for defining data types, constants, and APIs that generates idiomatic, type-safe code in TypeScript, Python, Java, C++, Kotlin, and Dart from a single .skir file. It includes built-in schema evolution safety, RPC support similar to gRPC, and serialization to JSON or binary formats.

Reflect MCP Server Implements Reflexion Paper for Persistent Coding Agent Memory
A developer implemented the Reflexion paper (Shinn et al., NeurIPS 2023) as an MCP server to give local coding agents persistent memory of their mistakes. The system uses regex-based pattern matching on error messages and stores lessons in SQLite with FTS5.

Agents Elements: A macOS Dashboard for Claude Code & Codex Installations
A native SwiftUI macOS app that scans ~/.claude and ~/.codex to show installed skills, subagents, commands, plugins, MCP servers, hooks, and session status with token usage.

Wisepanel MCP Server Enables Multi-LLM Deliberation in Claude Code and Cursor
Wisepanel released an MCP server that runs multi-agent deliberations directly from Claude Code, Cursor, or any MCP client, using a divergent context enhancement system with ChatGPT, Claude, Gemini, and Perplexity models.