
Analytical MCP Server
Analytical MCP Server: Enhancing AI with Structured Problem-Solving Tools
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?
- Analyzing datasets for insights and trends.
- Verifying research claims with reliable sources.
- 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.
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
- Clone the repository
- Install dependencies:
npm install
- 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
- 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 TypeScriptnpm test
: Run all testsnpm run test:integration
: Run integration tests onlynpm run test:exa
: Run Exa Research API testsnpm run test:research
: Run Research Verification testsnpm run test:server
: Run Server Tool Registration testsnpm run lint
: Check code qualitynpm run format
: Format codenpm 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
- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request
License
MIT License