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分析MCP服务器:使用结构化问题的工具增强AI

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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

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    Reviews

    4 (1)
    Avatar
    user_9fuQ5UsG
    2025-04-18

    As a dedicated user of analytical-mcp by quanticsoul4772, I've found it to be an invaluable tool for my data analysis tasks. Its comprehensive features and user-friendly interface make processing complex datasets more efficient and effective. Highly recommend it to anyone in need of robust analytical solutions! Check it out here: https://github.com/quanticsoul4772/analytical-mcp.