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MCP server · Science

io.github.archonics/mcp-audit

Free context-engineering audits for AI agents. BYOK Anthropic key. Top-3 findings per scan.

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About io.github.archonics/mcp-audit

io.github.archonics/mcp-audit is an MCP server in the Science category: free context-engineering audits for AI agents. BYOK Anthropic key. Top-3 findings per scan. It has been installed 0 times through Conduid.

Install

Claude Code
claude mcp add io-github-archonics-mcp-audit -- npx -y @archonics/mcp-audit
npx
npx -y @archonics/mcp-audit

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

Archonics MCP Audit Server

Free-tier context engineering audits for production AI agents, delivered as MCP tools you can call from Claude Desktop, Cursor, Claude Code, or any MCP-compatible client.

What you get: top-3 findings on your system prompts, tool definitions, or context packing, on demand, no account needed.

What it costs: nothing. The free scan is genuinely free. Upgrade paths to the $49 Instant Audit and $750 Full Audit are surfaced in the response footer; they're not paywalls on this tool.

Why this exists

Most production agent failures aren't model failures — they're context engineering failures. Ambiguous instructions, underspecified tools, bloated context, no regression tests on prompt changes. Those problems are spottable by a trained reader. Archonics has trained that reader and published it as an MCP tool so you can get a second opinion on your agent's context without filing a support ticket.

The underlying audit engine applies Archonics Audit Methodology v1.0, the same spec that drives our paid audits.

Tools

audit_system_prompt

Paste a system prompt. Get back the three most important context engineering issues in it, ranked by severity, with specific recommendations.

Covers: role clarity, instruction conflicts, negative space, priority structure when instructions conflict, token efficiency, format specification precision, failure-mode coverage.

audit_tool_definition

Paste a tool/function definition. Get back the three most important issues affecting how reliably the model will call it.

Covers: description quality (the "when to use this tool" question), parameter schema precision, parameter documentation, error response design, discoverability.

audit_context_packing

Paste a representative context payload (or describe it structurally). Get back the three most important efficiency and quality issues.

Covers: content inventory, redundancy across sections, freshness/relevance, ordering, truncation risk, prompt-cache utilization.

Installation

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "archonics-audit": {
      "command": "npx",
      "args": ["-y", "@archonics/mcp-audit"],
      "env": {
        "ANTHROPIC_API_KEY": "your-anthropic-api-key-here"
      }
    }
  }
}

Cursor

Add to your .cursor/mcp.json:

{
  "mcpServers": {
    "archonics-audit": {
      "command": "npx",
      "args": ["-y", "@archonics/mcp-audit"],
      "env": {
        "ANTHROPIC_API_KEY": "your-anthropic-api-key-here"
      }
    }
  }
}

Claude Code

claude mcp add archonics-audit npx -y @archonics/mcp-audit

Then set ANTHROPIC_API_KEY in your environment.

Why does it need my Anthropic API key?

The audit engine runs on Claude. You bring your own API key so:

  1. Audit submissions go directly from your machine to Anthropic's API, never through Archonics servers.
  2. Your costs are transparent — a typical audit uses 2,000–4,000 tokens, well under a penny.
  3. There's no "free but actually limited" rate-limit surprise. Your API key, your limits.

If you'd rather not bring your own key, use the $49 Instant Audit at agent.market — we cover the API costs and return a full-methodology audit PDF.

Privacy

Submitted content is processed ephemerally. No prospect content is retained on Archonics infrastructure or used to train any model. The API call pattern is: your client → your Anthropic API key → Anthropic → your client. Archonics servers are not in this path.

Aggregated, anonymized patterns across many audits may inform improvements to the methodology — "18 of 20 audited systems lacked prompt-regression tests" — but specific content never feeds that process.

Details: archonics.ai/privacy

Upgrade paths

If the free scan surfaces issues worth fixing, two paid tiers go deeper:

  • Instant Audit — $49 USDC via x402. Full methodology applied programmatically to a system you submit. 5-10 page PDF report covering all four dimensions (prompt, tools, context, eval) rather than just three findings in one dimension. Listed at agent.market/archonics.
  • Full Audit — $750. Human-reviewed audit of a complete agent system. 15-25 page report tuned to your team's context. Contact audits@archonics.ai.

Contact

License

MIT. Use it, fork it, audit yourself.

README mirrored from the source repository 4 months ago. The original is authoritative.

Questions

About io.github.archonics/mcp-audit

How do I install io.github.archonics/mcp-audit?

Run claude mcp add io-github-archonics-mcp-audit -- npx -y @archonics/mcp-audit, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is io.github.archonics/mcp-audit safe to use with an AI agent?

Its trust score is 37 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is io.github.archonics/mcp-audit still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.