Run a bounded sub-agent on the user's NVIDIA NIM account and return its written report.

Reach for this to keep large, mechanical, or exploratory work out of your own context: tracing how a feature flows across many files, auditing a directory for a pattern, summarising an unfamiliar module or dependency, drafting a migration plan, reviewing a diff. The sub-agent reads the repository itself and spends NIM tokens doing it; you only receive the finished report.

task must stand on its own. The sub-agent cannot see this conversation, your open files, the user's last message, or anything you have already worked out - it starts cold at the repo root. Spell out what to look at, what to produce, and what "done" means. Good: "Find every call site of load_config under submcp/ and list each as path:line with one line on how the result is used; answer as a markdown list." Bad: "look into that config thing we discussed".

Parameters: task - self-contained instructions, including the output format you want back. profile - "general" (default), "researcher", "coder", or "reviewer". Researcher for read-and-explain sweeps, coder for focused edits, reviewer for critique. files - paths to hand over up front so the sub-agent doesn't waste steps hunting. write - allow file edits. Off by default, and ignored entirely unless the server was started with SUBMCP_ALLOW_WRITE=1. Leave it off for investigation. model - override the NIM model for this run (default stepfun-ai/step-3.7-flash). max_steps - tool-call budget for this run (default 12).

Returns a markdown report: the sub-agent's findings, plus the model used, how many steps it took, which tools it called, and any files it changed. The sub-agent is sandboxed to the server's root directory, is read-only unless write=True, cannot run shell commands unless the operator enabled SUBMCP_ALLOW_SHELL, and refuses to read secrets (.env, private keys, credentials files).

For several independent subtasks, call delegate_parallel once instead of calling this tool repeatedly - it runs them concurrently over one connection.

Run several independent sub-agents at once and return every report in one answer.

This is the tool to use whenever the work splits into pieces that do not depend on each other: "summarise each of these four modules", "check these three services for the same misconfiguration", "for each failing test, find the cause". Running them concurrently on one NIM connection is much faster than calling delegate in a loop, and all the reading still happens outside your context.

Every string in tasks is a separate cold-start sub-agent with no memory of the others and no view of this conversation. Do not chain them - task 2 cannot use task 1's answer. If the work is genuinely sequential, use delegate one step at a time. Each task string must be self-contained and say what output you want, exactly as for delegate.

Parameters: tasks - list of self-contained task strings, one sub-agent each. profile - "general" (default), "researcher", "coder", or "reviewer"; applies to all. files - paths handed to every sub-agent up front. model - override the NIM model (default stepfun-ai/step-3.7-flash).

Concurrency is capped at SUBMCP_MAX_PARALLEL (default 4); extra tasks queue. All sub-agents are read-only here - there is no write parameter, because concurrent edits to one working tree are how you lose work. Use delegate with write=True for edits.

Returns one markdown document with a ## Task N section per input task, in the order you supplied them. A task that fails gets its own section marked FAILED with the reason; the other reports still come back intact, so one bad task never costs you the rest.

Show what SubMCP can do right now: profiles, model, sandbox root, and capability gates.

Call this before your first delegate in a session, or when a delegation behaves unexpectedly - it tells you which directory sub-agents are confined to, whether writes and shell are enabled, and what the step and timeout budgets are. Needs no API key, so it also works as a setup check: it will say plainly if NVIDIA_API_KEY is missing.