- name
- nat
- description
- NVIDIA NeMo Agent Toolkit (NAT) — install, create workflows, add tools, run agents, evaluate performance, and publish as A2A/MCP servers. Use when: (1) installing or setting up NAT, (2) creating or editing workflow YAML configs, (3) adding built-in or custom tools/functions, (4) running agents with
nat run, (5) evaluating or profiling workflows, (6) publishing workflows as A2A or MCP servers, (7) creating custom functions or function groups, (8) integrating with LangChain, LlamaIndex, CrewAI, or other frameworks. Trigger keywords: NAT, NeMo Agent Toolkit, nvidia-nat, nat run, nat workflow, nat eval, nat a2a, nat profiler, workflow.yml, react_agent, tool_calling_agent. - metadata
- { "openclaw": { "requires": { "anyBins": ["nat", "pip", "uv"] }, "primaryEnv": "NVIDIA_API_KEY" } }
NVIDIA NeMo Agent Toolkit (NAT)
A flexible library for connecting enterprise agents to data sources and tools across any framework.
- Repo: https://github.com/NVIDIA/NeMo-Agent-Toolkit
- Docs: https://docs.nvidia.com/nemo/agent-toolkit/latest/
Installation
# Core (pick one)
uv pip install nvidia-nat # recommended
pip install nvidia-nat
# With framework extras
uv pip install "nvidia-nat[langchain]" # LangChain/LangGraph
uv pip install "nvidia-nat[llama-index]" # LlamaIndex
uv pip install "nvidia-nat[crewai]" # CrewAI
uv pip install "nvidia-nat[mcp]" # MCP
uv pip install "nvidia-nat[a2a]" # A2A
uv pip install "nvidia-nat[mem0ai]" # Mem0 memory
uv pip install "nvidia-nat[eval,profiling]" # Eval + profiling
# Verify
nat --help && nat --versionFor development install from source, see references/install-from-source.md.
Quick Start
export NVIDIA_API_KEY=<key_from_build.nvidia.com>Create workflow.yml:
functions:
wikipedia_search:
_type: wiki_search
max_results: 2
llms:
nim_llm:
_type: nim
model_name: meta/llama-3.1-70b-instruct
temperature: 0.0
workflow:
_type: react_agent
tool_names: [wikipedia_search]
llm_name: nim_llm
verbose: true
parse_agent_response_max_retries: 3nat run --config_file workflow.yml --input "List five subspecies of Aardvarks"Workflow Configuration Structure
Four main YAML sections:
| Section | Purpose |
|---|---|
functions | Tools (web search, calculators, custom) |
llms | LLM provider configs (NIM, OpenAI, Azure, Bedrock) |
embedders | Embedding models for vector storage |
workflow | Agent type + wiring of tools and LLMs |
Agent Types (_type in workflow)
react_agent— Reasoning and actingreasoning_agent— Advanced reasoningrewwo_agent— Reasoning Without Observationresponses_api_agent— OpenAI Responses APItool_calling_agent— Direct tool callingautomatic_memory_wrapper_agent— Adds memoryrouter_agent— Routes to different workflowssequential_executor— Sequential tool execution
Built-in Tools (_type in functions)
wiki_search, webpage_query, tavily_internet_search, arxiv_search, current_datetime, calculator, text_file_ingest, and many more framework-specific tools.
List all available components:
nat info components -t function # Tools
nat info components -t llm_provider # LLMs
nat info components -t embedder # EmbeddersCommon CLI Commands
# Run workflow
nat run --config_file workflow.yml --input "question"
# Override params without editing YAML
nat run --config_file workflow.yml --input "question" \
--override llms.nim_llm.temperature 0.7 \
--override llms.nim_llm.model_name meta/llama-3.3-70b-instruct
# Create new workflow template
nat workflow create --workflow-dir examples my_workflow
# Evaluate
nat eval --config_file eval_config.yml
# Profile
nat profiler --config_file workflow.yml --input "test"
# Red team
nat red-team --config_file workflow.yml
# Workflow management
nat workflow reinstall my_workflow
nat workflow delete my_workflowCustom Tools and Function Groups
For creating custom tools, function groups, and advanced patterns, see:
- references/custom-tools.md — Writing custom functions, registration, and installation
- references/function-groups.md — Shared config, namespacing, include/exclude, access levels
A2A Server
Publish workflows as A2A agents for discovery and invocation by other A2A clients.
# Start A2A server
nat a2a serve --config_file workflow.yml
# Discover agent
nat a2a client discover --url http://localhost:10000
# Call agent
nat a2a client call --url http://localhost:10000 --message "What is 42 * 67?"For full A2A configuration (auth, concurrency, Kubernetes), see references/a2a-server.md.
Examples
The repo includes examples organized by category: Getting Started, Agents, Advanced Agents, Control Flow, Frameworks, MCP/A2A, Evaluation, and more. See references/examples.md for the full catalog and how to run them.
# Run any example
uv pip install -e examples/<example_directory>
nat run --config_file examples/<example_directory>/configs/config.yml --input "test"