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MCP verified MIT Self-run

MCP Scanner

mcp-knostic-mcp-scanner · by knostic

Advanced Shodan-based scanner for discovering, verifying, and enumerating Model Context Protocol (MCP) servers and AI infrastructure tools over HTTP & SSE.

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Install

$ agentstack add mcp-knostic-mcp-scanner

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • 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.

View the full security report →

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Passed review? Show it. Paste this badge into your README, it links to the public security report.

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
3mo ago

Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

MCP Scanner

> A Knostic Research Project > Advanced security research tool for discovering and analyzing Model Context Protocol (MCP) servers using the Shodan search engine.

Part of Knostic's ongoing research into AI infrastructure security and data governance.

⚠️ Important Disclaimer

This tool is designed for legitimate security research, authorized penetration testing, and educational purposes only.

  • Only scan systems you own or have explicit written permission to test
  • Respect rate limits and terms of service for all APIs used
  • Follow all applicable local, state, and federal laws
  • Be responsible and ethical in your security research

Knostic is committed to advancing AI security through responsible research practices.

🔍 What is MCP?

The Model Context Protocol (MCP) is an open protocol that enables secure connections between host applications (like Claude Desktop) and external data sources and tools. As enterprises increasingly adopt AI infrastructure, understanding the security posture of MCP deployments becomes critical for:

  • Data Governance: Ensuring sensitive information isn't exposed through misconfigured MCP servers
  • Attack Surface Management: Identifying publicly accessible AI infrastructure components
  • Compliance: Meeting regulatory requirements for AI system security
  • Risk Assessment: Understanding the broader AI ecosystem your organization interacts with

This scanner helps security professionals identify publicly exposed MCP servers for research and assessment purposes.

Features

  • Comprehensive Discovery: Uses 100+ Shodan search filters to find MCP servers
  • Multi-Transport Support: Tests both HTTP and Server-Sent Events (SSE) transports
  • Protocol Verification: Validates actual MCP protocol compliance
  • Tool Enumeration: Discovers available tools and capabilities
  • Detailed Reporting: Generates JSON, CSV, and summary reports
  • Rate Limiting: Built-in concurrent request limiting
  • Cross-Platform: Works on Windows, macOS, and Linux

🚀 Quick Start

Prerequisites

Installation

# Clone the repository
git clone https://github.com/knostic/MCP-Scanner.git
cd MCP-Scanner

# Install dependencies
pip install shodan requests aiohttp

# Or use requirements.txt if provided
pip install -r requirements.txt

Basic Usage

# Run the scanner
python mcp_scanner.py --api-key YOUR_SHODAN_API_KEY

# With custom options
python mcp_scanner.py --api-key YOUR_API_KEY --max-results 100 --max-concurrent 15 --output my_results.json

# Inspect specific servers
python mcp_func_checker.py --servers server1.com:8000,server2.com:3000

📊 Output

The scanner generates multiple output files:

  • mcp_scan_results_[timestamp]/verified_servers.json - Detailed server information
  • mcp_scan_results_[timestamp]/verified_servers.csv - CSV format for analysis
  • mcp_scan_results_[timestamp]/scan_summary.txt - Human-readable summary
  • mcp_discovery_[timestamp].log - Detailed execution logs

🛠️ Command Line Options

mcp_scanner.py

--api-key          Shodan API key (required)
--max-results      Maximum results per Shodan filter (default: 50)
--max-concurrent   Maximum concurrent connections (default: 10)
--output           Custom output filename prefix

mcpfuncchecker.py

--servers          Comma-separated list of servers to inspect
--file             File containing server list (one per line)
--timeout          Connection timeout in seconds (default: 10)
--output           Output filename for results

🔧 Advanced Usage

Custom Shodan Filters

The scanner uses 100+ predefined Shodan filters. You can modify the shodan_filters list in mcp_scanner.py to add custom search patterns.

Analyzing Results

import json

# Load scan results
with open('mcp_scan_results_timestamp/verified_servers.json', 'r') as f:
    servers = json.load(f)

# Analyze discovered tools
for server in servers:
    if 'tools' in server:
        print(f"Server: {server['url']}")
        print(f"Tools: {server['tools']}")

🔒 Security Research Applications

  • Exposed MCP Server Discovery: Find unintentionally public MCP servers
  • Configuration Analysis: Identify misconfigurations and security issues
  • Tool Enumeration: Catalog available tools and capabilities
  • Protocol Compliance Testing: Verify proper MCP implementation
  • Attack Surface Mapping: Understand MCP deployment patterns

🤝 Contributing

Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

🙏 Acknowledgments

  • Anthropic for the Model Context Protocol specification
  • Shodan for their excellent search engine API
  • The security research community for responsible disclosure practices

📚 Learn More

About MCP

About Knostic


Developed by Knostic - Leaders in AI Data Governance and Security

Remember: With great power comes great responsibility. Use this tool ethically and legally.

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.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.