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Independent project, not affiliated with Anthropic
stanfrbd avatar

Cyberbro MCP Server

stanfrbd/mcp-cyberbro
19authSTDIOregistry active
Summary

Connects Claude to Cyberbro, the open-source threat intelligence platform, for IOC extraction and reputation analysis. You get five tools: analyze observables (IPs, domains, URLs, hashes), check analysis status, pull results, list available engines, and grab shareable web URLs. Point it at your Cyberbro instance with a URL, then ask Claude to check indicators against engines like VirusTotal, Google Safe Browsing, or any custom modules you've configured. Useful when you're triaging alerts, enriching logs, or pivoting through IOCs during an investigation and want the context without leaving your editor. Supports stdio, SSE, and streamable HTTP transports. Ships as a Python package or Docker container.

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MseeP.ai Security Assessment Badge

Cyberbro MCP Server

5e5a4406 99c1 47f1 a726 de176baa824c
Extract IoCs from messy text and analyze them with Cyberbro.
🌐 demo.cyberbro.net

mcp-cyberbro-demo

Model Context Protocol server for Cyberbro.

This project is packaged as a standard Python distribution and can be launched with:

  • uvx mcp-cyberbro
  • pip install mcp-cyberbro then mcp-cyberbro

Why this server

  • Analyze observables (IP, domain, URL, hash, etc.) via Cyberbro engines.
  • Integrate threat-analysis actions directly in MCP-capable assistants.
  • Run with stdio, sse, or streamable-http transports.
  • Compatible with any MCP client that supports one of these transports.

Installation

Use with uvx (standalone)

uvx mcp-cyberbro --cyberbro_url http://localhost:5000

Use with pip

pip install mcp-cyberbro
mcp-cyberbro --cyberbro_url http://localhost:5000

Local development

pip install -e .
mcp-cyberbro --cyberbro_url http://localhost:5000

Docker

Default container command starts in streamable-http mode on port 8000.

docker run --rm -p 8000:8000 \
  -e CYBERBRO_URL=http://host.docker.internal:5000 \
  ghcr.io/stanfrbd/mcp-cyberbro:latest

To run in stdio mode, a custom Dockerfile is required:

FROM ghcr.io/stanfrbd/mcp-cyberbro:latest
CMD ["mcp-cyberbro", "--transport", "stdio"]

Build and use it:

docker build -t mcp-cyberbro-stdio .
docker run -i --rm -e CYBERBRO_URL=http://host.docker.internal:5000 mcp-cyberbro-stdio

Configuration

Copy .env.example and set at least:

  • CYBERBRO_URL (required)

Supported environment variables:

  • CYBERBRO_URL
  • API_PREFIX (default: api)
  • SSL_VERIFY (true/false)
  • MCP_TRANSPORT (stdio, sse, streamable-http)
  • MCP_HOST
  • MCP_PORT
  • MCP_MOUNT_PATH
  • MCP_SSE_PATH
  • MCP_STREAMABLE_HTTP_PATH

CLI flags are also available and override env values.

MCP Client Integration

You can use this server with Claude Desktop, Claude Code, Cursor, OpenAI-compatible MCP clients, or any other MCP client.

Example config using uvx:

{
  "mcpServers": {
    "cyberbro": {
      "command": "uvx",
      "args": ["mcp-cyberbro"],
      "env": {
        "CYBERBRO_URL": "http://localhost:5000"
      }
    }
  }
}

To use Docker with stdio transport (required by some MCP clients), build a custom image as shown in the Docker section above, then reference it:

{
  "mcpServers": {
    "cyberbro": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-e", "CYBERBRO_URL", "mcp-cyberbro-stdio"],
      "env": {
        "CYBERBRO_URL": "http://localhost:5000"
      }
    }
  }
}

Usage in VSCode - Example

Create .vscode/mcp.json

{
	"servers": {
		"mcp-cyberbro": {
			"type": "stdio",
			"command": "uvx",
			"args": [
				"mcp-cyberbro"
			],
			"env": {
				"CYBERBRO_URL": "http://127.0.0.1:5000"
			}
		}
	}
}

MCP Registry Metadata

server.json is included for MCP Registry publication and points to PyPI package mcp-cyberbro.

Release Pipelines

Release-created workflows:

  • .github/workflows/publish-test-pypi.yml
  • .github/workflows/publish-pypi.yml
  • .github/workflows/publish-mcp-plugin.yml

Available Tools

  • analyze_observable
  • is_analysis_complete
  • get_analysis_results
  • get_engines
  • get_web_url

Example Prompts

Here are practical prompt examples you can use with any MCP-capable assistant connected to Cyberbro.

Getting Indicator Details

  • Cyberbro: Check indicators for target.com
  • Can you check this IP reputation with Cyberbro? 192.168.1.1. Use github, google and virustotal engines.
  • I want to analyze the domain example.com. What can Cyberbro tell me about it? Use max 3 engines.
  • Analyze these observables with Cyberbro: suspicious-domain.com, 8.8.8.8, and 44d88612fea8a8f36de82e1278abb02f. Use all available engines.

Observable Analysis

  • I found this (hash|domain|url|ip|extension). Can you submit it for analysis to Cyberbro and analyze the results?

OSINT Investigation

  • Create an OSINT report for the domain example.com using Cyberbro. Use all available engines and pivot on the results for more information. Use a maximum of 10 analysis requests.

Acknowledgements

  • Model Context Protocol
  • MCP Python SDK
  • Cyberbro

License

MIT

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Configuration

CYBERBRO_URL*

Base URL of Cyberbro (for example http://localhost:5000)

API_PREFIX

Cyberbro API prefix (default: api)

SSL_VERIFY

Enable/disable SSL verification for Cyberbro API calls (true/false)

MCP_TRANSPORT

Transport override: stdio, sse or streamable-http

MCP_HOST

Host for HTTP transports

MCP_PORT

Port for HTTP transports

MCP_MOUNT_PATH

Mount path for SSE transport

MCP_SSE_PATH

SSE endpoint path

MCP_STREAMABLE_HTTP_PATH

Streamable HTTP endpoint path

Categories
Sales & Marketing
Registryactive
Packagemcp-cyberbro
TransportSTDIO
AuthRequired
UpdatedApr 25, 2026
View on GitHub

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