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Metal Mantra

Metal Mantra is a public registry providing automated evidence reports on AI agents. It offers insights into source findings, domain evidence, and explicit limits, helping users make informed decisions without claiming security certification.

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Metal Mantra screenshot
Metal Mantra screenshot

Metal Mantra serves as a public registry that offers automated evidence reports on AI agents. It is designed to provide users with insights into the source findings, domain evidence, and explicit limits of AI agents. The platform is built by Danhoangda, an independent AI lab based in Hanoi. Unlike other directories that rely on owner-provided information, Metal Mantra uses deterministic static rules to analyze public sources and publish evidence. Each report includes a score and grade across five weighted pillars: security and privacy, guardrails and loop control, schema and tooling, token and cost efficiency, and entity trust.

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The platform does not offer security certification; instead, it provides an automated signal based on a bounded snapshot of public source code. Metal Mantra does not use AI to score agents; the scores are derived from deterministic rules, ensuring consistent results from the same repository snapshot. AI is employed only in matching a buyer's plain-language job description to agents whose public descriptions may fit, without affecting the score.

Users can scan their own agents, with the first scan of a supported public GitHub repository being free. A re-audit pass costs $29 for three re-scans of one repository. Private repositories can also be scanned without sharing the source by running the Metal Mantra scanner inside a GitHub Actions job. The platform also allows AI agents to query the registry through a read-only MCP server.

The method used by Metal Mantra is public, with every rule, severity, and weight listed on the Standard page. However, the scanner's code is not open source. Metal Mantra emphasizes the importance of trusting the evidence provided rather than relying on promotional pitches.

  • CategorySecurity & Privacy
  • Pricing ModelFreemium
  • DeploymentCloud
  • PlatformsGitHub

  • Public registry of AI agent reports

  • Deterministic static rule analysis

  • Five weighted pillars for scoring

  • Free initial scan for public repositories

  • Re-audit pass for $29

  • Private repository scanning via GitHub Actions

  • Read-only MCP server for agent queries

  • Public method disclosure

  1. Explore: Browse the public registry

  2. Scan: Submit a public GitHub repository

  3. Verify: Check domain ownership

  4. Re-audit: Purchase additional scans if needed

  • Agent Evaluation
  • Public Repository Scanning
  • Private Repository Scanning
  • Domain Verification
  • AI Agent Querying

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