Schema | Portfolio Data Analytics MCP Server

Portfolio Data Analytics MCP Server

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": false }
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
load_csvA	Register a dataset from CSV text. Returns the inferred schema. Args: name: a unique name for the dataset. csv_text: raw CSV content (comma-separated, first row is header).
list_datasetsA	List all registered datasets with their schema.
summaryC	Return summary statistics for a numeric column or whole dataset. Args: name: the dataset name.
filter_rowsA	Filter rows where `column` operator `value`, e.g. spend > 5000. Args: name: the dataset name. column: the numeric column to filter on. operator: one of '>', '<', '>=', '<=', '==', '!='. value: the threshold.
top_rowsA	Return the top-N rows sorted by `column` descending. Args: name: the dataset name. column: the column to sort by. n: how many rows to return (default 5).
correlationA	Return the Pearson correlation between two numeric columns. Args: name: the dataset name. col_a: first numeric column. col_b: second numeric column.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/VladimirBigunenko/python-portfolio'

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