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privacyfence/privacyfence

privacyfence/privacyfence

Open-source privacy and approval gateway between AI assistants and your business systems (MCP): human approval, local PII checks and audit for Gmail, Drive, Slack, Salesforce, Jira and more.
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Config template (adjust for your client)
claude mcp add privacyfence -- npx -y privacyfence
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
1 ★ · privacyfence/privacyfence · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 1 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository privacyfence/privacyfence;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals

PrivacyFence

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**AI access without giving AI the keys.** Approve the sensitive. Automate the routine.
PrivacyFence is an open-source privacy and approval gateway between AI assistants and your business systems. It connects MCP-compatible assistants such as Claude Desktop and Claude Code to Gmail, Google Drive, Calendar, Slack, Salesforce, Jira, Confluence, Telegram, and more.
PrivacyFence enforces, independently of the AI, what an assistant may see and do. Sensitive reads and consequential actions require human approval, while routine requests can be automated by policy. Optional PII detection runs locally before personal data reaches the AI, and every decision is audited.
PrivacyFence runs on an employee’s own computer (macOS, Windows, or Linux) or as a central deployment on infrastructure the organization controls, allowing web clients such as claude.ai to connect as well. Connector credentials stay with PrivacyFence, never with the AI client, and no data passes through PrivacyFence-operated servers — there are none.
**Website:** privacyfence.eu · **Download:** privacyfence.eu/download · **Docs:** privacyfence.eu/docs
Why
Giving an AI assistant access to Gmail, Drive, Slack or Salesforce usually means giving it a
standing permission and trusting it to use that permission well. Being allowed to read a record is
not the same as wanting it sent to an AI, and a tool name in a client's prompt says little about
what is about to change. PrivacyFence puts an independent control point between the assistant and
your systems: the AI asks, PrivacyFence decides, and you see what is at stake before it happens.
What it does
- **Human approval** for sensitive reads and for writes, on cards that show the actual content or
change, who is asking and why — not a raw tool name or JSON payload.
- **Local PII detection** before a read reaches the AI: likely personal data is highlighted, and it
sends the request to a card even when a rule would have let it through.
- **Policy-based automation**: narrow always-allow rules (a sender domain, a Drive folder, a Slack
channel, a Jira project) let routine requests run without a card.
- **An audit log** of every accepted, denied and automatically approved request, chained so that
an edit made without its key is detected.
- **Credentials stay with PrivacyFence.** On a packaged install it runs under its own service
account, so the AI client, which runs as you, cannot read them or approve its own request.
- **A defined set of connectors**, each tool with a gate fixed in code. PrivacyFence is not a
generic proxy for arbitrary MCP tools.
How it works
Claude Desktop connects through the PrivacyFence extension (PrivacyFence.mcpb); Claude Code and
other clients that speak Streamable HTTP connect to the local /mcp endpoint directly; in an
organization deployment, clients such as claude.ai, ChatGPT (Developer Mode) and Gemini Enterprise
sign in with OAuth through the organization's identity provider. How it works walks one read and one
write through, card by card.
Platforms
| Install | Runs on |
|---|---|
| macOS (.dmg) | macOS 13 or newer, Apple silicon |
| Windows (-setup.exe) | Windows 10 / Windows Server 2016 or newer, x64 |
| Linux (.deb) | Ubuntu 24.04, Debian 13 or newer, amd64 |
| Organization deployment | A Linux server with Python 3.11 or newer and systemd (pip install privacyfence) |
Source
awesome · https://github.com/privacyfence/privacyfence
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