Hi,
I've opened a PR adding three NSE scripts and two shared nselibs to detect and 
enumerate two classes of AI infrastructure that nmap doesn't currently cover:

  *   mcp-info (discovery, safe, version) + mcp-enum (discovery, safe): MCP 
server detection (initialize handshake over Streamable HTTP + legacy SSE), 
OAuth 2.1 protected-resource discovery (RFC 9728), and read-only 
tools/resources/prompts enumeration with schema-based risk flagging.
  *   llm-info (discovery, safe): LLM inference API detection across the common 
frameworks (OpenAI-compatible/vLLM/SGLang, Ollama, HF TGI/TEI, llama.cpp, 
KoboldCpp, Triton/KServe, TorchServe, Anthropic) plus common AI web UIs, with 
order-independent identification, auth-state and model enumeration, and 
information-leak flagging.
  *   nselib/mcp.lua + nselib/llm.lua: shared transports / detectors / 
enumeration.

Read-only by default (MCP never calls tools/call; llm-info sends at most one 
minimal "hello" completion, disabled with llm.probe=false). Field-tested 
against FastMCP, server-everything, live public MCP servers (incl. OAuth-gated 
GitHub/Sentry/Linear), and real Ollama, KoboldCpp, and Open WebUI instances. 
Bundled mocks + regression matrices (23 MCP, 57 inference) in the standalone 
repo: https://github.com/insidetrust/nmap-ai-recon
Offered under the NPSL with the standard contribution terms. Happy to revise 
per review.
Thanks, Ben Williams (NCC Group)
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