MCP-Data-Analysis-Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
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.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| poisson_probabilityA | Calculate Poisson probability with different types. Args: lam: Lambda parameter (rate parameter, average events per interval) k: Number of events prob_type: Type of probability ("point", "cumulative", "survival") Returns: Dictionary with probability value and distribution info |
| descriptive_statisticsB | Calculate comprehensive descriptive statistics for a dataset. Args: data: List of numerical values Returns: Dictionary with various statistical measures |
| normal_probabilityB | Calculate normal distribution probabilities. Args: x: Value to calculate probability for mean: Mean of the normal distribution std_dev: Standard deviation of the normal distribution prob_type: Type of probability ("point", "cumulative", "survival") Returns: Dictionary with probability value and distribution info |
| correlation_analysisC | Perform correlation analysis between two datasets. Args: x_data: First dataset y_data: Second dataset Returns: Dictionary with correlation coefficients and analysis |
| hypothesis_test_ttestB | Perform one-sample t-test. Args: sample_data: Sample data for testing population_mean: Hypothesized population mean alpha: Significance level Returns: Dictionary with test results |
| linear_regression_analysisB | Perform simple linear regression analysis. Args: x_data: Independent variable data y_data: Dependent variable data Returns: Dictionary with regression results |
| data_summary_from_csv_textA | Generate summary statistics from CSV text data. Args: csv_text: CSV data as text delimiter: CSV delimiter Returns: Dictionary with data summary and statistics |
| binomial_probabilityA | Calculate binomial probability. Args: n: Number of trials k: Number of successes p: Probability of success on each trial prob_type: Type of probability ("point", "cumulative", "survival") Returns: Dictionary with probability value and distribution info |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Each tool targets a distinct statistical operation. The three probability distributions are clearly differentiated by parameter sets, and descriptive_statistics vs data_summary_from_csv_text differ by input format (list vs CSV text). No two tools have overlapping purposes.
All tool names use snake_case and are descriptive, but they follow inconsistent patterns (e.g., distribution_probability vs analysis vs statistics). The name 'hypothesis_test_ttest' is redundant. This is a minor deviation from a consistent convention.
8 tools is well-scoped for a statistical analysis server, covering probability distributions, descriptive stats, correlation, regression, and hypothesis testing without being bloated.
The server covers core statistical analyses but has notable gaps. It only includes one hypothesis test (one-sample t-test), lacks two-sample tests, ANOVA, chi-square, and multiple regression. Correlation analysis doesn't provide significance testing. For a server named 'Data-Analysis', this is incomplete but covers the basics.