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perplexityai
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perplexityai/numbat

Visibility into AI agent activity on endpoints, with on-device detection, optional pre-action blocking, and forensic reconstruction.

Go ◇ agent-security Apache-2.0
★1.1KSTARS
⑂120FORKS
!8ISSUES
🏆#5,888GLOBAL RANK
🔥2DAYS TRENDING
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Momentum

+28

STARS · LAST 30 DAYS

1

PER DAY

#684

MOST-STARRED Go

Window7 days30 days90 days
Stars gained+7+28+90
Per day111
Forks gained+1+3+10

numbat gained 28 stars in the last 30 days, about 1 a day, and now has 1.1K. It is about 1 year old and has averaged roughly 1.1K stars a year. It ranks #684 among Go repositories and #5,888 across all languages on GitHubRepo.

Trending Record

numbat has maintained a continuous presence across global trending indexes, peaking at #7489. Below is the 30-day activity profile:

💡 Overview

numbat is an open-source project written in Go: Visibility into AI agent activity on endpoints, with on-device detection, optional pre-action blocking, and forensic reconstruction.

Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-security, ai-agent-security, ai-agents. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Go for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ go install github.com/perplexityai/numbat@latest

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Go >= 1.21 runtime environment

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

numbat coordinates its core functionality through a modular Go pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with numbat.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install numbat using your package manager: `go install github.com/perplexityai/numbat@latest`

2

Initialize your project workspace or configuration file for numbat.

3

Import numbat into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `numbat --help` to verify successful setup.

👍 Strengths

Active community backing with 1,125 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 license.
Built in Go for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Go and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

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👥 Who Should Use This

Developers and engineering teams building with Go, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

perplexityai/numbat is currently ranked #5,888 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#5,881 amap-cvlab/ABot-Recon Python ★ 1.1K Compare ↗
#5,881 ant-research/AntOmniEvo Python ★ 1.1K Compare ↗
#5,885 gf3/dotfiles Emacs Lisp ★ 1.1K Compare ↗
#5,885 apache/ofbiz-framework Java ★ 1.1K Compare ↗
#5,885 palkan/isolator Ruby ★ 1.1K Compare ↗
#5,888 perplexityai/numbat This Project Go ★ 1.1K
#5,888 berylliumsec/nebula Python ★ 1.1K Compare ↗
#5,890 danger/swift Swift ★ 1.1K Compare ↗
#5,891 hivemq/hivemq-mqtt-client Java ★ 1.1K Compare ↗
#5,891 localgpt-app/localgpt Rust ★ 1.1K Compare ↗
#5,891 LilMGenius/paperthin JavaScript ★ 1.1K Compare ↗
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Frequently Asked Questions

What does numbat do? +

Visibility into AI agent activity on endpoints, with on-device detection, optional pre-action blocking, and forensic reconstruction.

What language is numbat written in? +

The primary language is Go. Topics include: agent-security, ai-agent-security, ai-agents.

Is numbat actively maintained? +

Yes, the last recorded push was on Oct 16, 2026 with 8 open issues being tracked.

How many stars does numbat have? +

numbat has 1,125 stars and 120 forks on GitHub.

How does numbat rank among GitHub repositories? +

With 1,125 stars, perplexityai/numbat is ranked #5,888 globally across all repositories tracked on GitHubRepo and #684 among Go projects.

What license is numbat distributed under? +

The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.

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