Enables AI clients to securely control Linux and WSL2 systems over Streamable HTTP with Bearer token authentication, supporting command execution, background jobs, file operations, Docker management, system inspection, and audit log access with safety confirmations and path protections.

Enables MCP-compatible clients to plan, validate, generate, and deploy complete network topologies from natural-language instructions, including live deployment to a running network simulator and export to configuration or script files.

Enables a model to write short Python programs that call a wrapped MCP server's tools as async functions, rather than invoking them one at a time. The program runs in a locked-down Docker sandbox, and every tool call passes through a host-side bridge that enforces an allowlist, schema-validated arguments, call budgets, timeouts and output caps.

A self-hosted sandbox for red teams to test payloads against modern detection before deployment. MCP integration lets an LLM agent drive analysis end to end.

A growing collection of MCP servers bringing offensive security tools to AI assistants. Nmap, Ghidra, Nuclei, SQLMap, Hashcat and more.