semvec/pypi-packages huggingface dataset:
wolfram-alpha-mcp-server 0.1.1
A MCP server to connect to wolfram alpha API.
Requires Python: >=3.13

# MCP-wolfram-alpha

A MCP server to connect to wolfram alpha API.

<a href="https://glama.ai/mcp/servers/q5fud9cttp">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/q5fud9cttp/badge" />
</a>

## Components

### Prompts

This is analogous to the `!wa` bang in duckduckgo search.

```python
def wa(query: str) -> f"Use wolfram alpha to answer the following question: {query}"
```

### Tools

Query Wolfram Alpha api.

```python
def query_wolfram_alpha(query: str) -> str
```

## Configuration

You **must** set the `WOLFRAM_API_KEY` environment variable. Get an api ket from [Wolfram Alpha](https://products.wolframalpha.com/api).

This was tested with the full results API, but it might not be required.

```json
{
    "mcpServers": {
        "MCP-wolfram-alpha": {
            "command": "uv",
            "args": [
                "--directory",
                "C:\\Users\\root\\Documents\\MCP-wolfram-alpha",
                "run",
                "MCP-wolfram-alpha"
            ],
            "env": {
                "WOLFRAM_API_KEY": "your-app-id"
            }
        }
    }
}
```

## Development

### Debugging

Since the official MCP inspector does not have good environment support, I reccommend using wong2's [mcp-cli-inspector](https://github.com/wong2/mcp-cli).

Create a config.json file in the same style as claude desktop.

```json
{
    "mcpServers": {
        "MCP-wolfram-alpha": {
            "command": "uv",
            "args": [
                "--directory",
                "/full/path/to/MCP-wolfram-alpha",
                "run",
                "MCP-wolfram-alpha"
            ],
            "env": {
                "WOLFRAM_API_KEY": "your-app-id"
            }
        }
    }
}
```

Then run:

```bash
npx @wong2/mcp-cli -c .\config.json
```
financial-datasets-mcp-server 0.1.0
Add your description here
Requires Python: >=3.13

# Financial Datasets MCP Server

## Introduction

This is a Model Context Protocol (MCP) server that provides access to stock market data from [Financial Datasets](https://www.financialdatasets.ai/). 

It allows Claude and other AI assistants to retrieve income statements, balance sheets, cash flow statements, stock prices, and market news directly through the MCP interface.

## Available Tools

This MCP server provides the following tools:

- **get_income_statements**: Retrieve income statements for a stock
- **get_balance_sheets**: Retrieve balance sheets for stock
- **get_cash_flow_statements**: Retrieve cash flow statements for a stock
- **get_current_price**: Get the latest price information for a stock
- **get_prices**: Get historical stock prices with customizable date ranges and intervals
- **get_news**: Get the latest news for a stock

## Setup

### Prerequisites

- Python 3.10 or higher
- [uv](https://github.com/astral-sh/uv) package manager

### Installation

1. Clone this repository:
   ```bash
   git clone https://github.com/financial-datasets/mcp-server
   cd mcp-server
   ```

2. If you don't have uv installed, install it:
   ```bash
   # macOS/Linux
   curl -LsSf https://astral.sh/uv/install.sh | sh
   
   # Windows
   curl -LsSf https://astral.sh/uv/install.ps1 | powershell
   ```

3. Install dependencies:
   ```bash
   # Create virtual env and activate it
   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   
   # Install dependencies
   uv add "mcp[cli]" httpx  # On Windows: uv add mcp[cli] httpx

   ```

4. Set up environment variables:
   ```bash
   # Create .env file for your API keys
   cp .env.example .env

   # Set API key in .env
   FINANCIAL_DATASETS_API_KEY=your-financial-datasets-api-key
   ```

5. Run the server:
   ```bash
   uv run server.py
   ```

## Connecting to Claude Desktop

1. Install [Claude Desktop](https://claude.ai/desktop) if you haven't already

2. Create or edit the Claude Desktop configuration file:
   ```bash
   # macOS
   mkdir -p ~/Library/Application\ Support/Claude/
   nano ~/Library/Application\ Support/Claude/claude_desktop_config.json
   ```

3. Add the following configuration:
   ```json
   {
     "mcpServers": {
       "financial-datasets": {
         "command": "/path/to/uv",
         "args": [
           "--directory",
           "/absolute/path/to/financial-datasets-mcp",
           "run",
           "server.py"
         ]
       }
     }
   }
   ```
   
   Replace `/path/to/uv` with the result of `which uv` and `/absolute/path/to/financial-datasets-mcp` with the absolute path to this project.

4. Restart Claude Desktop

5. You should now see the financial tools available in Claude Desktop's tools menu (hammer icon)

6. Try asking Claude questions like:
   - "What are Apple's recent income statements?"
   - "Show me the current price of Tesla stock"
   - "Get historical prices for MSFT from 2024-01-01 to 2024-12-31"
estecopy 2.1.0
Python library to support the proprietary modeFRONTER software
Requires Python: >=3.8
Keywords: estecopy, ESTECO, modeFRONTIER, pyFRONTIER, optimization

Connect your Python interpreter with modeFRONTIER, the leading software for process automation and design optimization.

You need to have modeFRONTIER installed and start the pyFRONTIER app to enable the connection with your Python interpreter either locally or remotely. Install the `estecopy`  package on your machine to enable the data exchange between your Python interpreter and modeFRONTIER.

Provides the following modules:

- `pyfrontier` - module for configuring the connection to an open pyFRONTIER
- `estecopy.db` - module for handling data
- `estecopy.plan` - module for handling plans and running a project in process mode
- `estecopy.charts` - module for plotting charts in the Design Space
- `estecopy.rsm` - module for handling response surfaces
- `estecopy.info` - module for accessing some information on the modeFRONTIER project

Refer to modeFRONTIER documentation for further details on the use of these modules and on configuring the connection between estecopy and pyFRONTIER