MCP server for Cyberbro IOC extraction, enrichment and reputation analysis.
{
"mcpServers": {
"io-github-stanfrbd-mcp-cyberbro": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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MCP server for Cyberbro IOC extraction, enrichment and reputation analysis.
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
License not specified.
Is it maintained?
Commit history unknown.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
This server is missing a description. Tools and install config are also missing.If you've used it, help the community.
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Extract IoCs from messy text and analyze them with Cyberbro.
🌐 demo.cyberbro.net
Model Context Protocol server for Cyberbro.
This project is packaged as a standard Python distribution and can be launched with:
uvx mcp-cyberbropip install mcp-cyberbro then mcp-cyberbrostdio, sse, or streamable-http transports.uvx (standalone)uvx mcp-cyberbro --cyberbro_url http://localhost:5000
pippip install mcp-cyberbro
mcp-cyberbro --cyberbro_url http://localhost:5000
pip install -e .
mcp-cyberbro --cyberbro_url http://localhost:5000
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 force stdio transport:
docker run -i --rm \
-e CYBERBRO_URL=http://host.docker.internal:5000 \
ghcr.io/stanfrbd/mcp-cyberbro:latest \
--transport stdio
Copy .env.example and set at least:
CYBERBRO_URL (required)Supported environment variables:
CYBERBRO_URLAPI_PREFIX (default: api)SSL_VERIFY (true/false)MCP_TRANSPORT (stdio, sse, streamable-http)MCP_HOSTMCP_PORTMCP_MOUNT_PATHMCP_SSE_PATHMCP_STREAMABLE_HTTP_PATHCLI flags are also available and override env values.
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"
}
}
}
}
Example with Docker + stdio:
{
"mcpServers": {
"cyberbro": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CYBERBRO_URL",
"ghcr.io/stanfrbd/mcp-cyberbro:latest",
"--transport",
"stdio"
],
"env": {
"CYBERBRO_URL": "http://localhost:5000"
}
}
}
}
Create .vscode/mcp.json
{
"servers": {
"mcp-cyberbro": {
"type": "stdio",
"command": "uvx",
"args": [
"mcp-cyberbro"
],
"env": {
"CYBERBRO_URL": "http://127.0.0.1:5000"
}
}
}
}
server.json is included for MCP Registry publication and points to PyPI package mcp-cyberbro.
Release-created workflows:
.github/workflows/publish-test-pypi.yml.github/workflows/publish-pypi.yml.github/workflows/publish-mcp-plugin.ymlanalyze_observableis_analysis_completeget_analysis_resultsget_enginesget_web_urlHere are practical prompt examples you can use with any MCP-capable assistant connected to Cyberbro.