LibreAI / AI Agents / NeMo-Agent-Toolkit
// agents · NVIDIA/NeMo-Agent-Toolkit

NeMo-Agent-Toolkit

NVIDIA's toolkit for connecting, profiling and optimizing teams of AI agents — across any framework

★ 2.7k stars⑂ 780 forksApache-2.0updated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

NeMo-Agent-Toolkit is an open-source ai agents project by NVIDIA (NVIDIA/NeMo-Agent-Toolkit on GitHub). It has 2,661 GitHub stars and 780 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 8 October 2026.

GitHub stars
2,661
Forks
780
License
Apache-2.0
Last updated on GitHub
8 October 2026
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide what you need: build a new workflow, or instrument, profile and evaluate an agent you already have in another framework.

  2. Get the toolkit

    pip install nvidia-nat, adding the extra for your framework; clone the repo if you want the examples.

  3. Install and configure

    Write a workflow.yml defining functions (tools), LLMs and the workflow agent, and set your model key (e.g. NVIDIA_API_KEY for NVIDIA NIMs from build.nvidia.com).

  4. Run your first workflow

    Run nat run --config_file workflow.yml --input "..." and inspect the result, then open the built-in UI to chat with and debug the workflow.

// features

Why people love it

Framework agnostic

Works side-by-side with LangChain, LlamaIndex, CrewAI, Semantic Kernel, Google ADK and custom frameworks to add instrumentation without a rewrite.

Profiling and observability

Profile entire workflows from agent level down to individual tokens, trace execution and understand runtime behavior in production.

Evaluation and optimization

An offline evaluation system, a hyper-parameter and prompt optimizer, and reinforcement-learning fine-tuning support for agent-specific models.

Protocol support

Integrate MCP tools into agents or publish workflows as MCP servers (FastMCP publishing), and build distributed agent teams with the A2A protocol with authentication.

Performance primitives

Agent Performance Primitives accelerate graph frameworks (LangChain, CrewAI, Agno) with parallel execution, speculative branching and node-level priority routing.

Reusable components and UI

Build tools and workflows once and reuse them; a built-in chat UI lets you interact with agents and debug workflows visually.

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// run it

Run it yourself

  1. Clone the repo

    Clone the toolkit if you want the examples locally; the library installs from PyPI in step 2.

    git clone https://github.com/NVIDIA/NeMo-Agent-Toolkit.git
    cd NeMo-Agent-Toolkit
  2. Install from PyPI

    Install the core package, adding a framework extra such as [langchain] if needed (Python 3.11–3.13).

    pip install nvidia-nat
    # e.g. pip install "nvidia-nat[langchain]"
  3. Run the Hello World workflow

    Set your NVIDIA key, save the README's workflow.yml (a ReAct agent with a Wikipedia tool), and run it with the nat CLI.

    export NVIDIA_API_KEY=<your-key>
    nat run --config_file workflow.yml --input "List five subspecies of Aardvarks"
// use cases

What you can build

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// faq

Questions, answered

Who maintains the NeMo Agent Toolkit?

NVIDIA maintains it, as part of the NeMo ecosystem; docs are at docs.nvidia.com/nemo/agent-toolkit.

Is it free?

Yes, Apache-2.0 licensed. Models you call (NVIDIA NIMs or other providers) have their own pricing.

Does it need a paid API key?

The Hello World uses NVIDIA NIMs with an NVIDIA_API_KEY from build.nvidia.com; the toolkit itself works with the LLM providers you configure in your workflow.

How does it compare to LangSmith alone?

LangSmith-style tracing is one piece (and the toolkit integrates with LangSmith natively). The toolkit also adds workflow composition, profiling, evaluation, optimization and protocol publishing across frameworks.

How do I get started?

pip install nvidia-nat, write a workflow.yml, and run nat run — or open the Colab introduction notebook with no local setup.

// keep exploring

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// alternatives

Alternatives in AI Agents

The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if NeMo-Agent-Toolkit is not the right fit.

Get NeMo-Agent-Toolkit

Free and open — grab the source, star the repo, and start creating.