Statsource

Provides data source connectivity and statistical tools to analyze data and generate ML predictions via an MCP client.

python

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "jamie7893-statsource-mcp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "jamie78933/statsource-mcp"
      ],
      "env": {
        "API_KEY": "YOUR_STATSOURCE_API_KEY",
        "DB_SOURCE_TYPE": "database",
        "DB_CONNECTION_STRING": "postgresql://username:password@host:5432/your_db"
      }
    }
  }
}

You operate a Statsource MCP Server to analyze data, calculate statistics, and generate ML predictions through an analytics API. This server lets you feed data from CSV, databases, or APIs and obtain statistical insights or predictive outputs for your models and applications.

How to use

To use the Statsource MCP Server, connect your MCP client and call the available tool to analyze data or produce predictions. Start by providing the columns you want to analyze or predict, and specify the data source if needed. You can filter, group, and time-filter data to focus on relevant subsets before computing statistics or generating forecasts.

How to install

Prerequisites you must have installed before running the server:

Docker (optional, for pre-built image)
Python or Node.js if you install from source (depending on your setup)

Option 1: Run with Docker (recommended)

docker pull jamie78933/statsource-mcp

docker run -i --rm jamie78933/statsource-mcp

Option 2: Install via Python package (if you prefer a local Python environment)

pip install mcp-server-stats

Then start the server with:

python -m mcp_server_stats

Available tools

get_statistics

Analyze data by calculating requested statistics or generating ML predictions based on specified parameters. This tool accepts data source details, columns to analyze, optional filters, groupings, and time constraints to produce descriptive statistics or predictions.

suggest_feature

Propose a new feature or improvement for the StatSource analytics platform with a clear description, use case, and optional priority.

Built by

VeilStrat

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