What runtime dependencies does YaraFlux MCP Server require?
Python 3.13+ is required for source installation. Docker is used for containerized deployment. No other external services are strictly required, but MinIO/S3 can be used for remote storage.
@ThreatFlux
基本情報
A yara based MCP Server
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"YaraFlux": {
"command": "docker",
"args": [
"pull",
"threatflux/yaraflux-mcp-server:latest"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
YaraFlux MCP Server is a Model Context Protocol (MCP) server that gives AI assistants the ability to analyze files using YARA rules. It integrates YARA-based threat scanning with LLMs, supporting comprehensive rule management, secure scanning, and result analysis through a modular architecture.
Run it with Docker (docker pull threatflux/yaraflux-mcp-server:latest and docker run with the required JWT_SECRET_KEY, ADMIN_PASSWORD, and DEBUG environment variables) or install from source (requires Python 3.13+, then make install and make run). For Claude Desktop, add a docker entry to claude_desktop_config.json with the appropriate environment variables and auto-approved tools.
Python 3.13+ is required for source installation. Docker is used for containerized deployment. No other external services are strictly required, but MinIO/S3 can be used for remote storage.
By default, uploaded files and scan results are stored on the local filesystem. Optionally, MinIO/S3 storage can be configured. JWT authentication protects the API, and the container runs as a non-root user.
The server uses the Model Context Protocol (MCP) for communication with AI assistants. API access is protected by JWT authentication, configured via the `JWT_SECRET_KEY` environment variable.
Yes, the `import_threatflux_rules` tool allows importing rules directly from the ThreatFlux GitHub repository, and rules can be categorized as custom or community.
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