semvec/pypi-packages huggingface dataset:
bilibili-mcp-tools 0.1.1
哔哩哔哩 MCP 服务器 - 支持搜索、弹幕、用户信息等功能的模型上下文协议服务器
License: MIT
Requires Python: >=3.9
Keywords: api, bilibili, b站, danmaku, mcp, search, 弹幕

# Bilibili API MCP Server

用于哔哩哔哩 API 的 MCP（模型上下文协议）服务器，支持多种操作。

## 环境要求

- [uv](https://docs.astral.sh/uv/) - 一个项目管理工具，可以很方便管理依赖。

## 使用方法

1. clone 本项目

2. 使用 uv 安装依赖

```bash
uv sync
```

3. 在任意 mcp client 中配置本 Server

```json
{
  "mcpServers": {
    "bilibili": {
      "command": "uv",
      "args": [
        "--directory",
        "/your-project-path/bilibili-mcp-server",
        "run",
        "bilibili.py"
      ]
    }
  }
}
```

4. 在 client 中使用

## 支持的操作

支持以下操作：

1. `general_search`: 基础搜索功能，使用关键词在哔哩哔哩进行搜索。
2. `search_user`: 专门用于搜索哔哩哔哩用户的功能，可以按照粉丝数排序。
3. `get_precise_results`: 精确搜索功能，可以过滤掉不必要的信息，支持多种搜索类型：
   - 用户搜索 (`user`)：精确匹配用户名，只返回完全匹配的结果。例如搜索"双雷"只会返回用户名为"双雷"的账号信息，不会返回其他相关用户
   - 视频搜索 (`video`)
   - 直播搜索 (`live`)
   - 专栏搜索 (`article`)
返回结果包含 `exact_match` 字段，标识是否找到精确匹配的结果。
4. `get_video_danmaku·`: 获取视频弹幕信息。

## 如何为本项目做贡献

1. Fork 本项目
2. 新建分支，并在新的分支上做改动
3. 提交 PR

## 🎉 更新内容

本项目现在包含了完整的打包和部署解决方案：

### 📦 打包选项

1. **Python包打包**（推荐）
   ```bash
   python build.py
   pip install dist/*.whl
   ```

2. **Docker容器化**
   ```bash
   docker build -t bilibili-mcp-server .
   docker-compose up -d
   ```

3. **自动化安装**
   ```bash
   python install.py
   ```

### 🚀 快速开始

```bash
# 1. 自动安装和配置
python install.py

# 2. 或者手动构建
python build.py

# 3. 运行演示
python example.py
```

### 📋 生成的配置文件

- `mcp_config.json` - 开发模式配置 (uv run)
- `mcp_config_pip.json` - pip安装模式配置
- `mcp_config_uvx.json` - uvx运行配置 (推荐)
- `mcp_config_wheel.json` - 直接从wheel包运行
- `docker-compose.yml` - Docker部署配置
- `Dockerfile` - 容器构建文件

### 📚 详细文档

查看 [`PACKAGING.md`](./PACKAGING.md) 获取完整的打包指南和使用说明。

## License

MIT
chempp 0.1.4
Chem++ for Chemical System Programming
License: MIT
Requires Python: >=3.7

# Chem++

**Chem++** is a domain-specific programming language and runtime for computational chemistry,
integrating a C++-like syntax with chemistry-specific types and functions and optional
PubChem lookup support. This package provides:

- A fully functional interpreter (`chempp.interpreter`) for the Chem++ language.
- A Safe API wrapper (`chempp.safe_api`) that enforces Parse → Analyze → Interpret order,
  provides PubChem caching + fallback, and exposes synchronous and asynchronous run helpers.
- A chemistry registry with common types (Atom, Molecule, Reaction) and helper functions.
- Toolkit features for Jupyter notebook integration, static analysis hooks, and a small cache.

## Quickstart

```python
import chempp.safe_api as cs

code = '''
float main() {
   print 2+3;
}
'''
# synchronous run
result = cs.run(code)

# asynchronous run (useful in notebooks)
import asyncio
asyncio.run(cs.run_async(code))
mitsuba-scene-description 0.1.0
Generated, typed, autocompletable Python API for composing Mitsuba scenes.
License: MIT
Requires Python: >=3.9

# Mitsuba Scene Description (MSD)

_Disclaimer: Expect rough edges and frequent changes to the API._

This package contains:
1) A **core runtime API** (`mitsuba_scene_description`) with typed dataclasses, a recursive serializer,
   and a small sample of common plugins (BSDFs, shapes, sensors, emitters, integrators, textures).
   You can use this immediately to build scenes programmatically and call `mi.load_dict(scene.to_dict())`.

2) A **generator script** (`generator/generate_mitsuba_api.py`) that **scrapes the official Mitsuba
   plugin reference** and generates modules per category with conservative typing.
   Run it locally (with internet access) to create a *complete* API for all plugins.

## Quick start (core API sample)

```python
from pprint import pprint
import mitsuba as mi
mi.set_variant("llvm_ad_rgb")

import mitsuba_scene_description as msd

red = msd.SmoothDiffuseMaterial(reflectance=msd.RGB([0.8, 0.2, 0.2]))
ball = msd.Sphere(
    radius=1.0,
    bsdf=red,
    to_world=msd.Transform().translate(0, 0, 3).scale(1.0, 1.0, 1.0),
)

cam = msd.PerspectivePinholeCamera(
    fov=45,
    to_world=msd.Transform().look_at(origin=[0, 1, -6], target=[0, 0, 0], up=[0, 1, 0]),
)
integrator = msd.PathTracer()
sun = msd.PointLightSource(
    to_world=msd.Transform().translate(3, 4, 2), intensity=msd.RGB([3, 3, 3])
)

scene = msd.Scene(
    integrator=integrator,
    sensor=cam,
    shapes={"ball": ball},
    emitters={"sun": sun},
)


pprint(scene.to_dict())
mi_scene = mi.load_dict(scene.to_dict())
rndr = mi.render(mi_scene)
mi.util.write_bitmap("test.png", rndr)
```

## Generate the full API from docs

1. Install requirements: `pip install requests beautifulsoup4`
2. Run the generator:
   ```bash
   python generator/generate_mitsuba_api.py --out gen --overview https://mitsuba.readthedocs.io/en/latest/src/plugin_reference.html
   ```

### Notes
- The generator uses **conservative typing by default** (`Optional[Plugin]` for unknown or nested plugin params).
- You can tweak typing, categories, and output via CLI flags (`--aggressive`, `--single-file`, `--categories`).

### Roadmap
- [ ] Post-processing of generation using the tree-sitter API to remove artifacts
- [ ] Versioning