Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@ai-security-gateway-mcp Scan this prompt for PII before I send it: my email is john.doe@example.com"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Local PII detection and masking for Claude Desktop, Cursor, and Windsurf. Your prompts are scanned on your machine before reaching any LLM.
Automatically detects and masks sensitive data in your prompts:
📧 Email addresses
📱 Phone numbers (India-friendly)
💳 Credit card numbers
🪪 Aadhaar numbers
📋 PAN cards
🌐 IP addresses
🛂 Passport numbers
🏦 Bank account numbers
Related MCP server: privacyscrubber-mcp
Once installed, Claude Desktop (and Cursor/Windsurf) automatically has access to a scan_prompt tool. You can ask Claude to scan any prompt before sending it, or Claude will proactively suggest scanning when it detects potentially sensitive content.
Add to your claude_desktop_config.json:
{
"mcpServers": {
"ai-security-gateway": {
"command": "npx",
"args": ["-y", "ai-security-gateway-mcp"]
}
}
}npm install -g ai-security-gateway-mcpThen add to claude_desktop_config.json:
{
"mcpServers": {
"ai-security-gateway": {
"command": "ai-security-gateway-mcp"
}
}
}macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
After restarting Claude Desktop, try:
Scan this prompt for PII before I send it: [your text here]Use REPLACE mode to anonymize: [your text here]Is this safe to send to an LLM? [your text here]Mode | Behaviour | Example |
| Partially hides values |
|
| Removes values entirely | (empty) |
| Substitutes typed tokens |
|
Claude Desktop (macOS and Windows)
Cursor
Windsurf
Any MCP-compatible client
All detection runs locally on your machine. No data is sent to any server or cloud service.
npm install
npm run build # compile TypeScript → dist/
npm run dev # run via tsx (no compile step)
npm start # run compiled outputWeb app (v1): https://github.com/dceptev-byte/ai_security_gateway
Scans text for PII (personally identifiable information) before sending to an LLM. Detects emails, phone numbers, credit cards, Aadhaar numbers, PAN cards, IP addresses, passports, and bank accounts. Returns risk level, findings, and anonymized text. Always run this before sending sensitive prompts to any LLM.
Inputs: text (required), mode.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 1 tool
With only one tool, there is no possibility of confusion between tools. The single tool's purpose is clearly defined and distinct.
The tool name 'scan_prompt' follows a clear verb_noun convention, which is consistent even though there is only one tool. No conflicting naming styles are present.
The server is named 'ai-security-gateway', implying a broader set of security functions, but it exposes only a single tool. This feels far too thin for the apparent scope, which likely requires multiple operations like output scanning or configuration.
The server only scans input prompts for PII and anonymizes them. It lacks other critical gateway features such as output scanning, response filtering, or policy management, making the surface severely incomplete for a security gateway.
Detect and redact PII and secrets (API keys, tokens) in text, HTML or PDF before it reaches an LLM.
Detect and redact PII and secrets before text reaches an LLM, with reversible placeholders.
Find and redact leaked secrets, wallet keys and PII before an AI agent sends text.
Scan prompts for injection attacks, redact PII, and audit LLM SDK usage from any MCP client
