Analytical MCP Server

Analytical MCP Server

By quanticsoul4772 GitHub

Analytical MCP Server: Enhancing AI with Structured Problem-Solving Tools

mathgpt math-solver
Overview

what is Analytical MCP Server?

Analytical MCP Server is a specialized Model Context Protocol (MCP) server that enhances AI capabilities with structured problem-solving tools, focusing on advanced analytical and natural language processing functionalities.

how to use Analytical MCP Server?

To use the Analytical MCP Server, clone the repository, install the necessary dependencies, set up your environment variables with the required API keys, and run the desired analytical or NLP tools using specific parameters.

key features of Analytical MCP Server?

  • Advanced analytical tools for dataset, decision, correlation, regression, time series analysis, and hypothesis testing.
  • Enhanced natural language processing capabilities including fact extraction, named entity recognition, sentiment analysis, and more.

use cases of Analytical MCP Server?

  1. Analyzing datasets for insights and trends.
  2. Verifying research claims with reliable sources.
  3. Extracting entities and relationships from text for better understanding.

FAQ from Analytical MCP Server?

  • What technologies does the Analytical MCP Server use?

It uses TypeScript, Model Context Protocol SDK, Exa API for research and NLP, and various NLP libraries.

  • Is there a demo available for the NLP capabilities?

Yes! You can run the included NLP demo to see the advanced capabilities in action.

  • How do I contribute to the project?

You can fork the repository, create a feature branch, commit your changes, push to the branch, and create a Pull Request.

Content

Analytical MCP Server

A specialized Model Context Protocol (MCP) server providing advanced analytical, research, and natural language processing capabilities.

Key Features

Analytical Tools

  • Dataset Analysis
  • Decision Analysis
  • Correlation Analysis
  • Regression Analysis
  • Time Series Analysis
  • Hypothesis Testing

Advanced NLP Capabilities

  • Enhanced Fact Extraction
  • Named Entity Recognition
  • Coreference Resolution
  • Relationship Extraction
  • Sentiment Analysis
  • Text Similarity
  • Part of Speech Tagging
  • Lemmatization
  • Spell Checking

Installation

Prerequisites

  • Node.js (v20+)
  • npm
  • Exa API key (for research and advanced NLP capabilities)

Setup

  1. Clone the repository
  2. Install dependencies:
    npm install
    
  3. Set up your environment variables:
    # Copy the example environment file
    cp .env.example .env
    
    # Edit .env and add your API keys
    # You'll need an Exa API key for research functionality
    
  4. Build the project:
    npm run build
    

Usage

Running Tools

Each tool can be invoked with specific parameters. Example:

// Analyze a dataset
const datasetAnalysis = await analyzeDataset([1, 2, 3, 4, 5], 'summary');

// Verify research claims
const researchVerification = await researchVerification.verifyResearch({
  query: 'Climate change impacts',
  sources: 3
});

// Extract entities from text
const entities = await advancedNER.recognizeEntities(
  "Apple Inc. is planning to open a new headquarters in Austin, Texas."
);

Advanced NLP Demo

You can run the included NLP demo to see the advanced capabilities in action:

npm run build
node examples/advanced_nlp_demo.js

Development

Available Scripts

  • npm run build: Compile TypeScript
  • npm test: Run all tests
  • npm run test:integration: Run integration tests only
  • npm run test:exa: Run Exa Research API tests
  • npm run test:research: Run Research Verification tests
  • npm run test:server: Run Server Tool Registration tests
  • npm run lint: Check code quality
  • npm run format: Format code
  • npm run nlp:demo: Run advanced NLP demo

Test Scripts

We provide dedicated scripts for running specific test suites:

Unix/Linux/Mac

# Run all integration tests with a summary report
./tools/run-all-integration-tests.sh

# Run specific test suites
./tools/run-exa-tests.sh
./tools/run-research-tests.sh
./tools/run-server-tests.sh
./tools/run-api-key-tests.sh
./tools/run-data-pipeline-tests.sh
./tools/run-market-analysis-tests.sh

Windows

# Run all integration tests with a summary report
.\tools\run-all-integration-tests.bat

Key Technologies

  • TypeScript
  • Model Context Protocol SDK
  • Exa API for Research and NLP
  • Natural Language Processing libraries
  • Jest for Testing

Advanced NLP Implementation

The Analytical MCP Server implements advanced NLP features using:

  • Exa research API for context-aware entity recognition
  • Natural language toolkit for basic NLP operations
  • Custom rule-based fallback mechanisms for offline capabilities
  • Enhanced fact extraction with confidence scoring
  • Relationship extraction between entities

For detailed information, see the Advanced NLP documentation.

Required API Keys

This project requires the following API key:

  • EXA_API_KEY: Used for research integration and advanced NLP

The .env.example file contains all available configuration options:

  • API keys
  • Feature flags
  • Cache settings
  • NLP configuration
  • Server configuration

Copy this file to .env in your project root and update with your actual API keys to get started.

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

MIT License

No tools information available.

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