S

Statsource MCP

Statsource MCP Server is a Model Context Protocol server that provides statistical analysis and machine learning prediction functions, supporting access to multiple data sources and diverse statistical calculations.
2 points
4

What is Statsource MCP Server?

Statsource MCP Server is a server based on the Model Context Protocol (MCP). It provides statistical analysis and machine learning prediction capabilities by connecting to various data sources (such as databases, CSV files, or APIs). AI models can use this tool to conduct in - depth data analysis and generate predictions.

How to use Statsource MCP Server?

You can start data analysis by uploading files, connecting to databases, or specifying API endpoints. The server supports a variety of statistical calculations and prediction tasks. You can select appropriate parameters to execute tasks according to your needs.

Applicable scenarios

Suitable for enterprise and individual users who need to quickly analyze data trends, generate prediction reports, or optimize business decisions.

Main features

Data statistical analysisSupports a variety of statistical indicators, such as mean, median, standard deviation, maximum, and minimum values.
Machine learning predictionCan generate future trend predictions based on historical data.
Flexible data source supportCompatible with multiple data sources, including CSV files, database tables, and API interfaces.
Filtering and groupingAllows users to refine the analysis scope through conditional filtering and grouping operations.

Advantages and limitations

Advantages
Powerful statistical analysis capabilities
Supports seamless integration of multiple data sources
Easy to use and feature - rich
Limitations
Advanced features may require professional knowledge
The processing speed may be slow for very large data sets

How to use

Installation and startup
Select the installation method (Docker, PIP, or direct run) according to your environment. Ensure that the necessary environment variables are configured.
Prepare data
Upload a CSV file or pass the database connection string to the server.
Execute analysis
Submit a request after setting the required parameters to obtain statistical results or predictions.

Usage examples

Case 1: Sales data analysisAnalyze the sales data of the past year to determine the best product categories.
Case 2: Future demand predictionPredict the demand for the next quarter based on historical order data.

Frequently Asked Questions

How to upload a CSV file?
Does it support custom filtering conditions?

Related resources

Official documentation
Comprehensively understand the functions and usage of Statsource MCP Server.
GitHub repository
View the source code and contribution opportunities.
Tutorial video
Quick start guide.
Installation
Copy the following command to your Client for configuration
"mcpServers": {
  "statsource": {
    "command": "uvx",
    "args": ["mcp-server-stats"]
  }
}

{
  "mcpServers": {
    "statsource": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "API_KEY=YOUR_STATSOURCE_API_KEY",
        "-e",
        "DB_CONNECTION_STRING=postgresql://your_db_user:your_db_password@your_db_host:5432/your_db_name",
        "-e",
        "DB_SOURCE_TYPE=database",
        "jamie78933/statsource-mcp"
      ],
      "protocolVersion": "2024-11-05"
    }
  }
}

"mcpServers": {
  "statsource": {
    "command": "python",
    "args": ["-m", "mcp_server_stats"]
  }
}

"mcpServers": {
  "statsource": {
    "command": "python",
    "args": ["-m", "mcp_server_stats"],
    "env": {
      "API_KEY": "your_api_key",
      "DB_CONNECTION_STRING": "postgresql://username:password@localhost:5432/your_db",
      "DB_SOURCE_TYPE": "database"
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.
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