技能潮 SkillTide 提交收录
官方说明7 个来源MCP 服务8 天前
tobocop2/lilbee

tobocop2/lilbee

Index files, code and crawled websites and answ
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add lilbee -- npx -y lilbee
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
66 ★ · tobocop2/lilbee · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 66 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 tobocop2/lilbee;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

The whole local AI stack in one executable: it runs and manages the models, and

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

Project site  ·  Tutorial reels  ·  PyPI  ·  Obsidian plugin  ·  REST API  ·  Chat (#lilbee)
  
lilbee runs and manages your models: chat, embedding, vision, and rerank, placed across every GPU you have. It puts them to work as a search engine you can talk to, over your files, notes, code, and the web, where every answer cites the exact file and line. It crawls websites into your library, launches your coding agents on local models, and hands any MCP-aware agent cited answers from everything you've indexed. The same engine backs the Obsidian community plugin, so your vault gets all of it without a terminal. Ask in plain English. No containers, no networking, nothing else to install or set up.
And it is private. Your files, the index, the embeddings, your questions, and the answers stay on your machine. lilbee sends no telemetry and needs no account. It contacts a cloud provider only when you set an API key for it, in lilbee's settings or in the provider's own environment variable. Then it checks once that the key works, and sends your questions only to a cloud model you pick.
It's all one program: no separate model server, vector database, or container to stand up. lilbee runs the models and keeps the index itself. Reach it as a terminal app, CLI, Model Context Protocol server, HTTP API, or Python library. Close it and it's gone, or run it as a service to keep it warm. Everything runs on your computer; it uses a cloud model only when you pick one.
Models are no different: lilbee has its own model manager and multi-GPU fleet, built on llama.cpp, so one executable does everything (browse Hugging Face, download a model, give it a role, run it on Metal / Vulkan / CUDA). You don't need Ollama or LM Studio at all: the architectures lilbee runs are behind most of the 190,000+ GGUF repos on Hugging Face, with representatives verified on real GPUs. If you already use them, point lilbee at your existing setup and keep your models.
> **Tutorial reel:** every demo on this page, plus the extras that don't fit here, with long-form captions at **lilbee.sh/tutorial**.
> ## ⚠️ Beta software
>
> lilbee is in **active beta** development. Every release on PyPI is a pre-release; you must use --pre (or uv's --prerelease=allow) when installing. Interfaces, command names, and on-disk formats may shift between betas. Feedback, bug reports, and issues are very welcome; that's the whole point of the beta.
>
> Latest pre-release (always): lilbee on PyPI →
---
- Quick start
- Tutorial reel (long-form videos)
- Install
- Hardware requirements
- Highlights
- Why lilbee
- First start
- What you can do with it
- Agents
- TUI
- HTTP Server · REST API reference
- Supported formats
- Wiki
- Built on
---
Install
**Two routes, and the difference matters:**
- **A self-contained bundle** (start here): the standalone binary, or the Homebrew / AUR / Nix / Docker / Flatpak / Snap / Scoop builds that wrap it. It carries its own Python runtime, llama.cpp, the model engine, and the optional extras, so there is nothing else to install and nothing to assemble. The trade-off is one large download and a small cold-start cost the first time it self-extracts.
- **Into your own Python** with pip or uv (Python 3.11 to 3.14), in its own section below. This is the developer route: it installs lilbee as a library in an environment you manage, and the model engine is a separate extra from a separate index that you have to ask for. Take it if you are working on lilbee or importing it into your own code.
Have a discrete GPU? The bundled builds and the Vulkan engine already use it. There are faster vendor builds too: NVIDIA (CUDA) and AMD (ROCm).
No external services either way; lilbee downloads and runs models locally. Optional, for scanned-PDF / image OCR: Tesseract (brew install tesseract / apt install tesseract-ocr) or a GGUF vision model.
| How | Command | Notes |
| --------------------- | ---------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Homebrew** | brew tap tobocop2/lilbee && brew install lilbee | macOS (Apple silicon and Intel) / Linux x86_64. Bundled build; clears the macOS quarantine flag for you. |
| **AUR** | paru -S lilbee | Arch Linux. Wraps the Linux x86_64 binary; works with yay / pacaur / any helper. |
来源
awesome · https://github.com/tobocop2/lilbee
按领域浏览
MCP 服务
Traction
66 ★
收录于
昨天

更多MCP 服务

查看MCP 服务全部 5,525 条 →

所属领域与标签

每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。

浏览全部领域 →

← 返回索引