Membro
Membro is a local-first memory service for AI assistants, providing MCP tools to recall ranked memories, search history, save memory notes, and retrieve a profile summary. Everything is stored in a local SQLite file with per-fact provenance and a review queue.
README
Membro
Membro is a local-first memory service for AI assistants. It ingests your conversations (including a claude.ai export), mines them for durable facts behind deterministic extraction walls, and serves the result to local models through a small HTTP API and an MCP server: ranked recall, verbatim history search, and a rebuilt profile summary with per-fact provenance. Everything lives in one SQLite file on your machine. Nothing listens beyond loopback unless you deliberately widen it to your own tailnet.
Guarantees
- Facts are superseded, quarantined, or dismissed, never deleted by automation. The only hard delete is a button in the UI.
- Every mined fact passes grounding, temporal, and source-trust checks before entering canon. Doubtful facts are held for your review.
- Ingested messages are immutable. The summary is a cache rebuilt from the ledger, and each claim traces to its source facts.
- With no API keys, ingest, search, and keyword recall still work; LLM paths raise clear errors instead of degrading silently.
Requirements
- Python 3.12+
- Optional: an Anthropic key (mining, summaries) and an OpenAI key (embeddings for semantic recall).
Quick start
git clone https://github.com/shawn-durrani/membro.git
cd membro
./start.sh
The server runs at http://127.0.0.1:8901; set MEMORY_PORT if that
port is taken. First run prints a recovery secret; use it once to enrol a
password, then log in with the password. Set MEMORY_AUTH_TOKEN in
.env to keep the secret stable.
To import your claude.ai export, unzip it first: the importer reads the
unzipped directory, not the zip. Stop the service before running it, or
point --data-dir at a throwaway copy. The only guard is a coarse one:
with no --data-dir, the importer quits if anything answers on
127.0.0.1:8901, and that port is hardcoded, so a service on another
MEMORY_PORT goes undetected. Pass --data-dir and there is no check at
all; it writes wherever you point it, running service or not.
unzip ~/Downloads/data-2026-08-01.zip -d ~/claude-export
.venv/bin/python scripts/import_claude_export.py --export-dir ~/claude-export
Imports are idempotent; re-running never duplicates messages.
MCP
claude mcp add -s user membro -e PYTHONPATH=<repo> -- <repo>/.venv/bin/python -m memory_service.mcp_server
Four tools: recall_memory, search_history, save_memory,
memory_summary. MCP saves carry an mcp:* origin and are always
quarantined for review; agents cannot write into canon.
memory_service.mcp_admin_server is a separate opt-in read-only pair
authenticated with the bearer token.
Review queue
Wall-flagged and untrusted facts wait in the web UI: approve, dismiss, quarantine, or supersede, all reversible. The miner scores importance 1 to 9; importance 10 never decays and only you can assign it. The Mathematics page shows the ledger as geometry and never shows fact content.
Operations
Snapshots land in data/backups/ on a timer with rotation and an
optional mirror folder (MEMORY_MIRROR_DIR).
ops/install-supervisor.sh installs a launchd agent; restart with
launchctl kickstart -k gui/$(id -u)/dev.membro.server. Everything the
service knows lives under data/; back that folder up and treat it as
sensitive.
Widening beyond loopback is tailnet-only and opt-in: read SECURITY.md first. Never expose the port to the open internet.
Docs
- ARCHITECTURE.md: the settled decisions.
- docs/MEMORY_DESIGN.md: the memory model.
- docs/MEMORY_INTEGRITY.md: the extraction walls.
- docs/API.md: the HTTP contract.
- docs/TUNING.md: every knob and its default.
- docs/TESTING.md: what the suite guarantees.
- docs/REFERENCES.md: research lineage, including claims we checked and rejected.
Licence
MIT.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。