NodeLLM 1.17: MCP Sampling, Concurrent Tool Execution, and Smarter ORM Control

Back when we introduced MCP support , we ended on a teaser: Phase 3 would tackle Sampling —letting servers request completions from the host instead of only exposing tools and resources to it. NodeLLM 1.17 delivers on that, and pairs it with a second, unrelated but overdue improvement: precise control over how tool calls execute, now available consistently in both core and the ORM persistence layer. 🔄 MCP Sampling: Closing the Loop Sampling inverts the usual MCP direction. Instead of the client asking the server for tools, the server asks the client to run an LLM completion on its behalf. This lets an MCP server offer LLM-powered capabilities—summarization, classification, drafting—without needing its own API key or provider integration. createLLMSamplingHandler answers those requests using a real NodeLLM instance, so a server's tool ends up powered by whatever model you configure client-side: import { createLLM } from " @node-llm/core " ; import { MCP , createLLMSamplingHandler } from " @node-llm/mcp " ; const llm = createLLM ({ provider : " openai " }); const mcp = await MCP . connect ( { command : " node " , args : [ " ./sampling-server.mjs " ] }, { sampling : createLLMSamplingHandler ( llm , " gpt-4o-mini " ) } ); const tools = await mcp . discoverTools (); // The server only advertises sampling-backed tools once it sees // the client declared sampling support during the handshake. If you need full control over how a sampling request is answered—routing by model hint, injecting your own guardrails—pass a plain handler function instead of { llm, model } . It receives the raw sampling/createMessage params and returns a CreateMessageResult , so you decide exactly how (or whether) to answer. ⚡ Concurrent Tool Execution When a model returns several independent tool calls in the same turn, NodeLLM has always executed them one at a time. That's safe by default, but wastes time when the calls don't depend on each other—three weather lookups for three different cities, s