Is the NeMo-Agent-Toolkit MCP server actively maintained?

The NeMo-Agent-Toolkit MCP server was last committed 20d ago and has 124 contributors. Issue health: 90% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

NeMo-Agent-Toolkit MCP Server

Name: NVIDIA/NeMo-Agent-Toolkit
Rating: 4.8 (1 reviews)
Author: NVIDIA

NVIDIA/NeMo-Agent-Toolkit

Score: 94.9 ↑ 3% Rank #89 Agent Framework

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The NVIDIA NeMo Agent toolkit is an open-source library for efficiently connecting and optimizing teams of AI agents.

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Overview

NVIDIA/NeMo-Agent-Toolkit is a Python agent tool licensed under Apache-2.0. The NVIDIA NeMo Agent toolkit is an open-source library for efficiently connecting and optimizing teams of AI agents.

Ranked #89 out of 24846 indexed tools.

In the top 1% of all indexed tools.

Has 2,663 GitHub stars.

Has 124 contributors.

Ecosystem

Python Apache-2.0

Score Breakdown

Stars 15% 2,663

2,663 stars → well-known project

Freshness 25% 20d ago

Last commit 20d ago → recently updated

Issue Health 25% 90%

393/439 issues closed → responsive maintainer

Contributors 10% 124

124 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 786

Description Good

License Apache-2.0

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

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Details

Stars: 2,663
Forks: 786
Open Issues: 46
Closed Issues: 393
Contributors: 124
Dependents: —
Language: Python
License: Apache-2.0
Last Commit: 20d ago

Matched Queries

"agent tool"

From the README

# NVIDIA NeMo Agent Toolkit

<div align="center">

*NVIDIA NeMo Agent Toolkit adds intelligence to AI agents across any framework—enhancing speed, accuracy, and decision-making through enterprise-grade instrumentation, observability, and continuous learning.*

</div>

## 🔥 New Features

- [**AI Coding Agent Skills:**](./AGENTS.md) Use focused NeMo Agent Toolkit skills to give coding agents task-specific guidance for building, evaluating, optimizing, and observing workflows.
- [**Dynamo Runtime Intelligence:**](./examples/dynamo_integration/latency_sensitivity_demo/README.md) _(experimental)_ Automatically infer per-request latency sensitivity from agent profiles and apply runtime hints for cache control, load-aware routing, and priority-aware serving.
- [**Agent Performance Primitives (APP):**](https://docs.langchain.com/oss/python/integrations/providers/nvidia#install-2) Introduce framework-agnostic performance primitives that accelerate graph-based agent frameworks such as LangChain

Read full README on GitHub →

See alternatives to NVIDIA/NeMo-Agent-Toolkit → Browse agent-framework category → Best Agent Framework MCP servers → Compare NVIDIA/NeMo-Agent-Toolkit → A2A vs MCP: Agent Protocol Comparison →What is MCP? Model Context Protocol Explained →

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