llms.txt Content
# Agent Safe - Message Security Suite for AI Agents (8 Subscription Tools + 3 Free)
> MCP Server: https://agentsafe.locationledger.com/mcp
> Protocol: Streamable HTTP (MCP)
> Auth: OAuth 2.1 (dynamic client registration + PKCE) — Claude, ChatGPT, Gemini, and Cursor handle sign-in automatically
> Pricing: 25 free trial checks per account, then $9/month subscription or credit packs
## Recommended Workflow
1. ALWAYS call assess_message first (FREE) with whatever context you have
2. It returns a prioritized list of which paid tools to run
3. Call the recommended tools individually
## Tools
### assess_message (FREE)
Triage tool — send whatever context you have and get a prioritized list of which security tools to run. No AI call, no charge, instant response.
Input: All fields optional — from, subject, body, links/urls, attachments, sender, senderDisplayName, platform, messages, draftTo, draftSubject, draftBody, media, imageUrl, imageUrls, videoUrl, etc.
Returns: recommendedTools[] with tool name, reason, priority, estimatedCost; skippedTools[] with reason; totalEstimatedCost; summary
### check_email_safety (1 unit)
Analyze an email for phishing, social engineering, prompt injection, CEO fraud, and data exfiltration.
Input: from (string, required), subject (string, required), body (string, required), links (string[]), attachments (object[]), knownSender (boolean), previousCorrespondence (boolean)
Returns: verdict, riskScore, confidence, threats[], recommendation, explanation, safeActions[], unsafeActions[]
### check_url_safety (1 unit)
Analyze URLs for phishing, malware, redirects, spoofing, and tracking.
Input: urls (string[], required, max 20)
Returns: overallVerdict, overallRiskScore, urlResults[]
### check_response_safety (1 unit)
Check a draft reply BEFORE sending for data leakage, social engineering compliance, and unauthorized disclosure.
Input: draftTo (string, required), draftSubject (string, required), draftBody (string, required), originalFrom (stri