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Blind Auditor

mcp-sim-xia-blind-auditor · by Sim-xia

MCP tool for improving model coding quality by mandatory self-audition

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Install

$ agentstack add mcp-sim-xia-blind-auditor

Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.

Security review

⚠ Flagged

1 finding(s); flagged for manual review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures
  • high Pipes remote content directly into a shell (remote code execution).

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

🛡️ Blind Auditor - MCP Server

"Code -> audit -> amend -> audit again -> pass."

Blind Auditor is a mandatory code auditing system built on the MCP (Model Context Protocol). It uses a unique "Thinking Isolation" mechanism to force AI Agents to enter an independent "audit phase" and self-review their code before outputting the final result.

🧠 Core Philosophy: Thinking Isolation

Traditional AI coding is often "generate and output," which allows errors and biases to slip through. Blind Auditor introduces a middle layer:

  1. Intercept: When the Agent wants to output code, it must first submit it to Blind Auditor.
  2. Isolate: Blind Auditor does not return the result immediately. Instead, it injects a mandatory system instruction, forcing the Agent to pause its current persona and switch to a "Ruthless Auditor" role.
  3. Audit: In this isolated context, the Agent must scan the generated code line by line against the predefined rules.json.
  4. Release: The code is unlocked and returned to the user only when the audit score meets the threshold (default > 80) and there are no Critical issues.

🎯 Key Features

  • 🛡️ Zero Trust Architecture: Default distrust of the Agent's initial draft; it must pass an audit.
  • 💰 Zero Extra Cost: Reuses the host IDE's current session model, requiring no additional API Key.
  • ⚖️ Bias Removal: Forces a perspective switch via Prompt injection to break generation inertia.
  • 📏 Strict Compliance: Hard-codes team code standards (rules.json) into the generation process, which is more effective than simple Prompts.
  • 🔄 Auto-Fix Loop: Automatically triggers a "fix-resubmit" loop upon audit failure until compliance is met or the maximum retry count is reached.

🚀 Quick Start

1. Prerequisites

This project requires Python 3.10+ and uv.

# Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Enter project directory
cd blind-auditor

# Install dependencies (automatically creates virtual environment)
uv sync

2. Configure Audit Rules (rules.json)

Create or edit rules.json in the project root. This is the auditor's "Rulebook".

{
  "project_name": "MyCoreProject",
  "strict_mode": true,
  "max_retries": 3,
  "rules": [
    {
      "id": "SEC-001",
      "severity": "CRITICAL",
      "description": "Strictly prohibit hardcoding any API Keys, passwords, or sensitive Tokens.",
      "weight": 50
    },
    {
      "id": "PERF-001",
      "severity": "WARNING",
      "description": "Avoid database queries or IO operations inside loops.",
      "weight": 15
    },
    {
      "id": "STYLE-001",
      "severity": "PREFERENCE",
      "description": "Use snake_case for variable names.",
      "weight": 5
    }
  ]
}

Configuration Fields:

  • severity:
  • CRITICAL: Fatal error. If found, the audit fails immediately. Usually carries a high penalty.
  • WARNING: Warning. Moderate penalty; accumulation can lead to failure.
  • PREFERENCE: Style preference. Low penalty.
  • weight: The penalty points deducted when this rule is violated (Total score: 100).

3. Configure IDE (Antigravity / Cursor / Windsurf)

Step A: Add System Prompt (Critical)

To ensure the Agent knows it must use this tool, add the following instruction to your .cursorrules or IDE System Prompt settings:

# Blind Auditor Protocol
**CRITICAL INSTRUCTION**:
You are integrated with the **Blind Auditor MCP**.
Whenever you generate code for a user request, you **MUST NOT** output the code block directly to the user.

**Execution Protocol**:
1.  **Draft**: Generate the code internally in your thought process.
2.  **Submit**: Call the `submit_draft` tool with your code and language.
3.  **Obey**: The tool will return a strict "Audit Instruction". You MUST follow it exactly to audit your own code.
4.  **Finalize**: Only when the tool returns "✅ AUDIT PASSED" can you display the final code to the user.

**Prohibited**:
- Do NOT output code blocks before passing the audit.
- Do NOT skip the audit step for "simple" changes.
Step B: Configure MCP Server

Add the following to your MCP client configuration file (e.g., claude_desktop_config.json or IDE settings):

Note: Replace /path/to/your/blind-auditor with the actual absolute path where you cloned this repository.

{
  "mcpServers": {
    "blind-auditor": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/your/blind-auditor", "blind-auditor"]
    }
  }
}

🔧 Tool Details

1. submit_draft

Submit a code draft.

  • Input: code (content), language (programming language)
  • Behavior: Locks the session and returns mandatory audit instructions.

2. submit_audit_result

Submit your audit conclusion.

  • Input:
  • passed (bool): Whether you believe it passed.
  • issues (list): List of issues found.
  • score (int): Score from 0-100.
  • Behavior:
  • If `score Agent

Agent["Agent Generates Draft"] -->|1. submit_draft| MCP MCP -->|2. Inject Audit Instructions| Agent

subgraph Isolation ["Thinking Isolation"] Agent -->|3. Self-Review| Agent Agent -->|4. submitauditresult| MCP end

MCP -->|5. Verdict| Decision{"Passed?"}

Decision -->|No - Issues Found| Retry["Retry Count +1"] Retry -->|Limit Not Reached| Fix["Agent Fixes Code"] Fix -->|Resubmit| Agent

Decision -->|Yes - Score >= 80| Final["✅ Output Final Code"]

Retry -->|Limit Reached| Force["⚠️ Force Output - With Warning"]


## ❓ Troubleshooting

**Q: The Agent always outputs code directly without calling tools.**
A: Check if the System Prompt is configured correctly. You must explicitly tell the Agent "Do NOT output code directly". You can also manually remind it in the chat: "Please audit via Blind Auditor first".

**Q: Why does it fail even if I give the code 100 points?**
A: Check if any `CRITICAL` rules in `rules.json` were triggered. Current logic mainly relies on the `score` passed by the Agent, but if `passed` is `True` while `score < 80`, the system will force a rejection.

**Q: Which programming languages are supported?**
A: Theoretically, all languages are supported. Blind Auditor itself does not parse code syntax but relies on the Agent's understanding to match descriptions in `rules.json`.

---

## 🛠️ Development Guide

```bash
# Run server
uv run blind-auditor

# Or run directly with Python module
uv run python -m src.main

# Debug mode (output to stderr)
# View print statements in src/main.py

📄 License

MIT License

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.