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Analytical MCP Server

by quanticsoul4772
GitHub
TypeScript
MIT License
  • Linux
  • Apple
OverviewInspectNewSchemaRelated ServersReviewsScore
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Integrations

  • Integrated for environment variable management, allowing configuration of API keys, feature flags, cache settings, NLP and server settings through a .env file

  • Integrated for testing capabilities, supporting various test suites including integration tests, Exa Research API tests, and server tool registration tests

  • Required as the runtime environment for the MCP server, specifically version 20 or higher

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

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

Provides advanced analytical, research, and natural language processing capabilities through a Model Context Protocol server, enabling dataset analysis, decision analysis, and enhanced NLP features like entity recognition and fact extraction.

  1. Key Features
    1. Analytical Tools
    2. Advanced NLP Capabilities
  2. Installation
    1. Prerequisites
    2. Setup
  3. Usage
    1. Running Tools
    2. Advanced NLP Demo
  4. Development
    1. Available Scripts
    2. Test Scripts
    3. Key Technologies
  5. Advanced NLP Implementation
    1. Required API Keys
      1. Contributing
        1. License

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