mcp server data exploration
Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.
Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.
MCP Server is a versatile tool designed for interactive data exploration.
Your personal Data Scientist assistant, turning complex datasets into clear, actionable insights.
Get it here
Install and Set Up
On macOS, run the following command in your terminal:
python setup.py
Load Templates and Tools
Once the server is running, wait for the prompt template and tools to load in Claude Desktop.
Start Exploring
csv_path
: Local path to the CSV filetopic
: The topic of exploration (e.g., "Weather patterns in New York" or "Housing prices in California")These are examples of how you can use MCP Server to explore data without any human intervention.
Arguments:
csv_path
(string, required): Path to the CSV filedf_name
(string, optional): Name for the DataFrame. Defaults to df_1, df_2, etc., if not providedrun-script
script
(string, required): The script to execute~/Library/Application Support/Claude/claude_desktop_config.json
%APPDATA%/Claude/claude_desktop_config.json
"mcpServers": {
"mcp-server-ds": {
"command": "uv",
"args": [
"--directory",
"/Users/username/src/mcp-server-ds",
"run",
"mcp-server-ds"
]
}
}
"mcpServers": {
"mcp-server-ds": {
"command": "uvx",
"args": [
"mcp-server-ds"
]
}
}
Sync Dependencies
uv sync
Build Distributions
uv build
Generates source and wheel distributions in the dist/ directory.
Publish to PyPI
uv publish
Contributions are welcome! Whether you're fixing bugs, adding features, or improving documentation, your help makes this project better.
If you encounter bugs or have suggestions, open an issue in the issues section. Include: - Steps to reproduce (if applicable) - Expected vs. actual behavior - Screenshots or error logs (if relevant)
This project is licensed under the MIT License. See the LICENSE file for details.
Questions? Feedback? Open an issue or reach out to the maintainers. Let's make this project awesome together!
This is an open source project run by ReadingPlus.AI LLC. and open to contributions from the entire community.
[
{
"description": "nLoad CSV File ToolnnPurpose:nLoad a local CSV file into a DataFrame.nnUsage Notes:ntâ¢tIf a df_name is not provided, the tool will automatically assign names sequentially as df_1, df_2, and so on.n",
"inputSchema": {
"properties": {
"csv_path": {
"title": "Csv Path",
"type": "string"
},
"df_name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": {
"path": "uv.lock",
"type": "blob"
},
"title": "Df Name"
}
},
"required": [
"csv_path"
],
"title": "LoadCsv",
"type": "object"
},
"name": "load_csv"
},
{
"description": "nPython Script Execution ToolnnPurpose:nExecute Python scripts for specific data analytics tasks.nnAllowed Actionsnt1.tPrint Results: Output will be displayed as the scriptâs stdout.nt2.t[Optional] Save DataFrames: Store DataFrames in memory for future use by specifying a save_to_memory name.nnProhibited Actionsnt1.tOverwriting Original DataFrames: Do not modify existing DataFrames to preserve their integrity for future tasks.nt2.tCreating Charts: Chart generation is not permitted.n",
"inputSchema": {
"properties": {
"save_to_memory": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": {
"path": "uv.lock",
"type": "blob"
},
"title": "Save To Memory"
},
"script": {
"title": "Script",
"type": "string"
}
},
"required": [
"script"
],
"title": "RunScript",
"type": "object"
},
"name": "run_script"
}
]