MCP 服务器

JeffersonStats

Enables comprehensive statistical analysis including descriptive statistics, hypothesis testing, regression, and more via a FastMCP-based API.

README

JeffersonStats: Advanced Statistical Analysis MCP Server

Overview

JeffersonStats is a powerful, high-performance statistical analysis server built on the FastMCP framework. It provides a comprehensive suite of statistical tools accessible via a clean, intuitive API. Whether you're performing basic descriptive statistics or advanced statistical tests, JeffersonStats delivers accurate results with minimal configuration.

Features

JeffersonStats offers a rich set of statistical capabilities:

Basic Statistics

Mean, median, mode, and range calculations
Standard deviation and variance
Quartiles and interquartile range (IQR)
Percentile and quantile calculations

Advanced Statistics

Skewness and kurtosis analysis
Correlation coefficients (Pearson, Spearman, Kendall's tau)
Covariance calculations
Z-score transformations

Hypothesis Testing

T-tests (one-sample, independent, paired)
ANOVA (Analysis of Variance)
Chi-square tests
Mann-Whitney U test
Wilcoxon signed-rank test
Normality tests (Shapiro-Wilk)
Binomial tests

Data Analysis

Linear regression
Confidence intervals (standard and bootstrap)
Outlier detection
Moving averages
Frequency tables
Comprehensive descriptive statistics summaries

Why Choose JeffersonStats?

High Performance: Built on optimized NumPy and SciPy libraries for fast computation
Easy Integration: Simple HTTP API that works with any programming language or platform
Comprehensive: Over 30 statistical tools in a single package
Reliable: Based on industry-standard statistical implementations
Containerized: Easy deployment with Docker
Scalable: Designed to handle large datasets efficiently

Installation

Using Python

# Clone the repository
git clone https://github.com/yourusername/JeffersonStats.git
cd JeffersonStats

# Create a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run the server
python mcpserver.py

Using Docker

# Clone the repository
git clone https://github.com/yourusername/JeffersonStats.git
cd JeffersonStats

# Build the Docker image
docker build -t jeffersonstats:latest .

# Run the container
docker run -p 8080:8080 jeffersonstats

The server will be available at http://localhost:8080.