Blind-Audition-MCP
A zero-cost MCP server that forces AI to self-correct code using prompt injection and context isolation.
README
🛡️ Blind Auditor - MCP Server
一个基于 MCP 协议的代码自动审计工具,通过"思维隔离"强制 AI Agent 在生成代码后进行自我审查。
WARN: 这个项目处于非常早期的开发阶段,所以稳定性和功能性可能欠佳
🎯 核心特性
- 零成本: 复用宿主 IDE 的推理模型,无需额外 API Key
- 去偏见: 通过 Prompt 注入强制 Agent 切换"审计员"角色
- 强合规: 将团队代码规范(
rules.json)硬性植入生成流程 - 自动循环: 审计失败时自动触发代码修正,最多重试 3 次
- 强执行性: 当使用此MCP时,MCP规则拥有比对话提示词的绝对更高优先级
🚀 快速开始
1. 安装依赖
cd blind-auditor
uv sync
2. 配置规则
编辑 rules.json 文件,定义您的审计规则:
{
"project_name": "MyProject",
"strict_mode": true,
"max_retries": 3,
"rules": [
{
"id": "SEC-001",
"severity": "CRITICAL",
"description": "严禁硬编码 API Key 或密码"
}
]
}
3. 配置 IDE
Antigravity / Cursor
在项目根目录创建 .cursorrules 或在 IDE 设置中添加 System Prompt:
**Critical Instruction**:
Whenever you generate code for a user request, you MUST NOT output it directly.
You MUST interact with the `Blind Auditor` MCP tool:
1. Generate the code internally.
2. Call `submit_draft` with the code.
3. Follow the instructions returned by the tool strictly.
MCP 服务器配置
在 MCP 客户端配置文件中添加:
{
"mcpServers": {
"blind-auditor": {
"command": "python",
"args": ["-m", "src.main"],
"cwd": "/path/to/blind-auditor"
}
}
}
🔧 工具说明
submit_draft
提交代码草稿进行审计。
参数:
code(str): 完整的代码内容language(str): 编程语言,如python,typescript
返回: 审计指令或熔断放行
submit_audit_result
提交审计结果。
参数:
passed(bool): 是否通过审计issues(list[str]): 发现的问题列表score(int): 质量评分 (0-100)
返回: 放行代码或修复指令
reset_session
重置当前审计会话。
🔁 工作流程
graph TD
A[Agent 生成代码] --> B[调用 submit_draft]
B --> C{检查重试次数}
C -->|超限| D[强制放行]
C -->|未超限| E[进入审计模式]
E --> F[Agent 审查代码]
F --> G[调用 submit_audit_result]
G --> H{审计结果}
H -->|通过| I[放行代码]
H -->|失败| J[重试计数+1]
J --> K[返回修复指令]
K --> A
📝 规则配置
严重等级
- CRITICAL: 阻断性问题(如安全漏洞)
- WARNING: 警告性问题(如代码质量)
- PREFERENCE: 偏好性问题(如代码风格)
权重系统
weight 字段用于计算综合评分,范围 0-100。
🛠️ 开发
运行 MCP 服务器
python -m src.main
测试
# 使用 MCP Inspector 测试
npx @anthropic-ai/mcp-inspector python -m src.main
📄 许可证
MIT License
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
E2B
Using MCP to run code via e2b.