NVIDIA NeMo Agent Toolkit
by NVIDIA
Official listing: built and published by NVIDIA. More from NVIDIA
Connects, profiles, evaluates, and optimizes agent workflows across frameworks like LangChain, LlamaIndex, and CrewAI, with MCP and A2A support and a `nat` CLI for Python developers.
Use it now
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Try this first
Ask your assistant, with NVIDIA NeMo Agent Toolkit connected:
- Run and Serve Workflows
Use NVIDIA NeMo Agent Toolkit to run YAML-defined agent workflows: ‹what you need›
- Workflow Evaluation
Use NVIDIA NeMo Agent Toolkit to score the accuracy of agent workflows against datasets: ‹what you need›
- Parameter and Prompt Optimizer
Use NVIDIA NeMo Agent Toolkit to search hyperparameters: ‹what you're looking for›
Connect it over MCP
Connect NVIDIA NeMo Agent Toolkit as an MCP server, following its setup instructions at https://docs.nvidia.com/nemo/agent-toolkit/latest/get-started/quick-start.html
Setup guide: docs.nvidia.com/nemo/agent-toolkit/latest/get-started/quick…
Install the CLI
pip install nvidia-nat
Setup guide: docs.nvidia.com/nemo/agent-toolkit/latest/get-started/quick…
Call the API
Auth None needed
Setup guide: docs.nvidia.com/nemo/agent-toolkit/latest/get-started/quick…
Compare
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- Access
- APICLIMCP
- Auth
- None
- Skills
- 4
Skills
Run and Serve Workflows
Runs YAML-defined agent workflows with `nat run` or serves them over a FastAPI server with streaming endpoints via `nat serve`.
Workflow Evaluation
Scores the accuracy of agent workflows against datasets with `nat eval` and records performance characteristics per run.
Parameter and Prompt Optimizer
Searches hyperparameters with Optuna and evolves prompts with a genetic algorithm via `nat optimize` to hit chosen metrics.
MCP Client and Server
Consumes remote MCP tools inside workflows and publishes workflow functions as MCP tools with the `nat mcp serve` command.