by Beever-AI · MCP Server · ★ 245
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Your First LLM-Wiki Conversation Knowledge Base
| Stars | 245 |
| Forks | 30 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 35.75/100 |
| Open Issues | 18 |
| Last Updated | 2026-05-05 |
| Created | 2026-04-21 |
| Platforms | gemini, mcp, python |
| Est. Tokens | ~5736k |
These tools work well together with beever-atlas for enhanced workflows:
Looking for a beever-atlas alternative? If you're comparing beever-atlas with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Open Source Implementation of Karpathy's LLM Wiki. Upload documents, connect your Claude account via MCP, and
LLM-powered knowledge base from your Claude Code, Codex CLI, Copilot, Cursor & Gemini sessions. Karpathy's LLM
The Complete AI Development Toolkit for Claude Code — 103 skills, 36 agents, 172 hooks. Production-ready patte
AI Team OS — Multi-Agent Team Operating System for Claude Code. 40+ MCP tools, 22 agent templates, task wall,
This repo covers LLM, Agents, MCP Tools, Skills concepts with sample codes: LangChain & LangGraph, AWS Strands
Local memory infrastructure for AI agents. Store knowledge and skills in isolated vaults you compose, control
Explore other popular mcp server tools:
beever-atlas is Your First LLM-Wiki Conversation Knowledge Base. It is categorized as a MCP Server with 245 GitHub stars.
beever-atlas is primarily written in Python. It covers topics such as adk-google, agents, discord-bot.
You can find installation instructions and usage details in the beever-atlas GitHub repository at github.com/Beever-AI/beever-atlas. The project has 245 stars and 30 forks, indicating an active community.
beever-atlas is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to beever-atlas on Agent Skills Hub include llmwiki, llm-wiki, orchestkit. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.