semvec/pypi-packages huggingface dataset:
aimcp 0.1.2
AI-Enhanced MCP Tool Manager with intelligent tool description generation
License: MIT
Requires Python: >=3.8
Keywords: mcp, ai, tools, openai, model-context-protocol

# AIMCP - AI-Enhanced MCP Tool Manager

[![PyPI version](https://badge.fury.io/py/aimcp.svg)](https://badge.fury.io/py/aimcp)
[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

AIMCP 是一个基于 MCP (Model Context Protocol) 的工具管理器，主要用于统一管理和规范化工具描述。

## 主要功能

- 🤖 使用大语言模型自动生成标准化的工具描述
- 🔧 通过配置文件统一管理多个 MCP Server
- 📝 支持手动编辑工具描述（无需AI生成）
- 🌍 支持多语言工具描述

## 安装

```bash
pip install aimcp
```

## 快速开始

### 基本使用

```python
from aimcp import AIMCP
import asyncio

# 初始化客户端
client = AIMCP(
    mcp_config_path="./mcp_config.json",
    tools_config_path="./tools_config.json",
    api_key="your-api-key",  # 可选，也可通过环境变量设置
    model="gpt-4o-mini",
    language="中文"
)

# 生成工具配置
# ai_create=True：使用AI生成描述
# ai_create=False：使用原始描述，可后续手动修改
res = asyncio.run(client.create_aimcp_tools(ai_create=False))
```

### MCP配置示例

`mcp_config.json`:
```json
{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/allowed/files"],
      "env": {}
    }
  }
}
```

## 未来规划

- 工具路由功能
- 错误处理优化
- 更多服务端集成

## 许可证

MIT License
pyglimpse 0.1.0
A pandas DataFrame glimpse function inspired by R's dplyr::glimpse.
License: MIT
Requires Python: >=3.7

# pyglimpse

A pandas DataFrame glimpse function inspired by R's dplyr::glimpse.

## Installation

```bash
pip install pyglimpse
```

## Usage

```python
import pandas as pd
from pyglimpse import glimpse

df = pd.DataFrame({
    'a': [1, 2, 3],
    'b': ['x', 'y', 'z']
})
glimpse(df)
```
streamlit-autocomplete 0.1.0
Streamlit text_area autocomplete using streamlit-textcomplete
License: MIT
Requires Python: >=3.10.12

# streamlit_autocomplete

A simple Python package for adding **autocomplete** functionality to a Streamlit app’s `st.text_area`, using [`streamlit-textcomplete`](https://pypi.org/project/streamlit-textcomplete/).

## Features

- Fast, case‑insensitive autocomplete as you type
- Works with any list of strings (cities, stock names, etc.)
- Clean, minimal API for Streamlit

---

## Installation

```bash
pip install streamlit-autocomplete
```

> **Note:** `streamlit` and `streamlit-textcomplete` are installed automatically as dependencies.

---

## Usage

```python
import streamlit as st
from streamlit_autocomplete import st_textcomplete_autocomplete

# Autocomplete options
city_names = [
    "New York", "London", "Paris", "Berlin", "Tokyo", "Mumbai",
    # ...more
]

query = st_textcomplete_autocomplete(
    label="Enter city or metric",
    options=city_names,
    key="city_autocomplete",
    help="Start typing a city name"
)

st.write("You typed:", query)
```

---

## API

| Parameter             | Type | Description                                            |
| --------------------- | ---- | ------------------------------------------------------ |
| **label**       | str  | Label for the text area                                |
| **options**     | list | List of strings for autocomplete                       |
| **key**         | str  | Streamlit key (use different keys for multiple fields) |
| **placeholder** | str  | Placeholder text (optional)                            |
| **height**      | int  | Text area height (optional, default `120`)           |
| **help**        | str  | Help tooltip (optional)                                |
| **max_count**   | int  | Maximum suggestions to display (default `10`)        |

**Returns:** `str` – the current typed/autocompleted string.

---

## License

MIT License

---

## Credits

- [streamlit-textcomplete](https://github.com/huseinzol05/streamlit-textcomplete)