Skip to main content

A Model Context Protocol server for statistical analysis

Project description

Statsource MCP Server

A Model Context Protocol server that provides statistical analysis capabilities. This server enables LLMs to analyze data from various sources, calculate statistics, and generate predictions.

The statistics tool connects to our analytics API and allows AI models to perform statistical analysis and generate ML predictions based on user data, whether it's in a PostgreSQL database or a CSV file.

Available Tools

get_statistics

Analyze data and calculate statistics or generate ML predictions based on provided parameters.

Arguments:

  • columns (list of strings, required): List of column names to analyze or predict
  • data_source (string, optional): Path to data file, database connection string, or API endpoint
  • source_type (string, optional): Type of data source ("csv", "database", or "api")
  • statistics (list of strings, optional): List of statistics to calculate (for statistical analysis)
  • query_type (string, optional): Type of query ("statistics" or "ml_prediction")
  • periods (integer, optional): Number of future periods to predict (for ML predictions)

suggest_feature

Suggest a new feature or improvement for the StatSource analytics platform.

Arguments:

  • description (string, required): A clear, detailed description of the suggested feature
  • use_case (string, required): Explanation of how and why users would use this feature
  • priority (string, optional): Suggested priority level ("low", "medium", "high")

Installation

Using uv (recommended)

When using uv no specific installation is needed. We will use uvx to directly run mcp-server-stats.

Using PIP

Alternatively you can install mcp-server-stats via pip:

pip install mcp-server-stats

After installation, you can run it as a script using:

python -m mcp_server_stats

Or use the console script:

mcp-server-stats

Configuration

Configure for Claude.app

Add to your Claude settings:

Using uvx

"mcpServers": {
  "statsource": {
    "command": "uvx",
    "args": ["mcp-server-stats"]
  }
}

Using docker

"mcpServers": {
  "statsource": {
    "command": "docker",
    "args": ["run", "-i", "--rm", "statsource/mcp"]
  }
}

Using pip installation

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

Environment Variables

You can configure the server using environment variables in your Claude.app configuration:

"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"
    }
  }
}

Available environment variables:

  • API_KEY: Your API key for authentication with statsource.me
  • DB_CONNECTION_STRING: Default database connection string
  • DB_SOURCE_TYPE: Default data source type (usually "database")

Debugging

You can use the MCP inspector to debug the server. For uvx installations:

npx @modelcontextprotocol/inspector uvx mcp-server-stats

Or if you've installed the package in a specific directory or are developing on it:

cd path/to/servers/
npx @modelcontextprotocol/inspector python -m mcp_server_stats

Contributing

We encourage contributions to help expand and improve mcp-server-stats. Whether you want to add new tools, enhance existing functionality, or improve documentation, your input is valuable.

Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mcp-server-stats even more powerful and useful.

License

mcp-server-stats is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mcp_server_stats-0.1.6.tar.gz (8.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mcp_server_stats-0.1.6-py3-none-any.whl (8.8 kB view details)

Uploaded Python 3

File details

Details for the file mcp_server_stats-0.1.6.tar.gz.

File metadata

  • Download URL: mcp_server_stats-0.1.6.tar.gz
  • Upload date:
  • Size: 8.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.5

File hashes

Hashes for mcp_server_stats-0.1.6.tar.gz
Algorithm Hash digest
SHA256 3f599f9172bff0f9e2df4e59cf535faa29a9cc047e60564052037bb80cf8babb
MD5 a9630283ab0981fcc30eeb24ddda0b86
BLAKE2b-256 f29d4887a2ccb1c0412dcddd29d34f8e57cfc40e5d85913d5f6e527f0e4dbdb7

See more details on using hashes here.

File details

Details for the file mcp_server_stats-0.1.6-py3-none-any.whl.

File metadata

File hashes

Hashes for mcp_server_stats-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 86e86e16d659cf994a57c2954782591f2068f480641d2391ec159423189e5840
MD5 e60f5d0d488263124d68c3a78d89914c
BLAKE2b-256 a424c64a5f48d448e2f1c01706cfcd3515f9200a500273dba4cfacdafc5c5d5b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page