BambooAI — security grade SAFE, quality 72/100

Security audit verdict: SAFE · quality 72/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by pgalko · Agent Tool · ★ 791

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About BambooAI

BambooAI https://bambooai.org BambooAI is an open-source library that enables natural language-based data analysis using Large Language Models (LLMs). It works with both local datasets and can fetch data from external sources and APIs. Table of Contents Overview Features Demo Videos Installation Quick Start How It Works Configuration Parameters Agent and Model Configuration Auxiliary Datasets Dataframe Ontology (Semantic Memory) Vector DB (Episodic Memory) Usage Examples Web Application Setup Using Docker (Recommended) Using pip package Using complete repository Model Support Environment Variables Logging Performance Comparison Contributing Overview BambooAI is an experimental tool that makes data analysis more accessible by allowing users to interact with their data through natural language conversations. It's designed to: Process natural language q

aiai-agentsanthropicdata-analysisdata-sciencedockergeminigroqllmmistral

Quick Facts

Stars791
Forks86
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score71.7678635591703/100
Open Issues17
Last Updated2026-09-16
Created2023-05-07
Platformsdocker, gemini, python
Est. Tokens~547k

Compatible Skills

These tools work well together with BambooAI for enhanced workflows:

  • dbt-llm-agent — semantic(0.35)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)
  • RAGLight — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • table-transformer — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • promptmask — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • relevanceai — semantic(0.18)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)

BambooAI alternative? Top 6 similar tools

Looking for a BambooAI alternative? If you're comparing BambooAI with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • MakerAi by gustavoeenriquez · ⭐ 206

    The AI Operating System for Delphi. 100% native framework with RAG 2.0, autonomous agents, MCP protocol, and u

  • cai by ad-si · ⭐ 202

    User friendly CLI tool for AI tasks. Stop thinking about LLMs and prompts, start getting results!

  • kea-research by KeaBase · ⭐ 200

    KEA Research - Multi-AI collaboration platform that combines responses from multiple AI models, cross-validate

  • tools by strands-agents · ⭐ 1.3k

    A set of tools that gives agents powerful capabilities.

  • BaseAI by CommandCodeAI · ⭐ 1.3k

    BaseAI — The Web AI Framework. The easiest way to build serverless autonomous AI agents with memory. Start bui

  • sage by Storia-AI · ⭐ 1.3k

    Chat with any codebase in under two minutes | Fully local or via third-party APIs

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Frequently Asked Questions

What is BambooAI?

BambooAI is A Python library powered by Language Models (LLMs) for conversational data discovery and analysis.. It is categorized as a Agent Tool with 791 GitHub stars.

What programming language is BambooAI written in?

BambooAI is primarily written in Python. It covers topics such as ai, ai-agents, anthropic.

How do I install or use BambooAI?

You can find installation instructions and usage details in the BambooAI GitHub repository at github.com/pgalko/BambooAI. The project has 791 stars and 86 forks, indicating an active community.

What license does BambooAI use?

BambooAI is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to BambooAI?

The top alternatives to BambooAI on Agent Skills Hub include MakerAi, cai, kea-research. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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