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    Analytical Mcp

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

    4 stars
    TypeScript
    Updated Oct 14, 2025

    Table of Contents

    • Setup
    • Prerequisites
    • Installation
    • Option 1: Direct Installation
    • Option 2: Docker
    • Configuration
    • Direct Installation Configuration
    • Docker Configuration
    • Available Tools
    • Statistical Analysis
    • Decision Analysis
    • Logical Reasoning
    • Research Verification
    • Observability & Metrics
    • Metrics Endpoint
    • Available Metrics
    • Circuit Breaker Metrics
    • Cache Metrics
    • System Metrics
    • Configuration
    • Usage Examples
    • Usage Examples
    • Dataset Analysis
    • Decision Analysis
    • Logical Analysis
    • Development
    • Testing
    • Scripts
    • Project Structure
    • Tool Categories
    • Statistical Analysis
    • Decision Support
    • Logical Reasoning
    • Research Integration
    • Security and Privacy
    • License
    • Contributing
    • Troubleshooting
    • Common Issues
    • Debug Mode
    • Links

    Table of Contents

    • Setup
    • Prerequisites
    • Installation
    • Option 1: Direct Installation
    • Option 2: Docker
    • Configuration
    • Direct Installation Configuration
    • Docker Configuration
    • Available Tools
    • Statistical Analysis
    • Decision Analysis
    • Logical Reasoning
    • Research Verification
    • Observability & Metrics
    • Metrics Endpoint
    • Available Metrics
    • Circuit Breaker Metrics
    • Cache Metrics
    • System Metrics
    • Configuration
    • Usage Examples
    • Usage Examples
    • Dataset Analysis
    • Decision Analysis
    • Logical Analysis
    • Development
    • Testing
    • Scripts
    • Project Structure
    • Tool Categories
    • Statistical Analysis
    • Decision Support
    • Logical Reasoning
    • Research Integration
    • Security and Privacy
    • License
    • Contributing
    • Troubleshooting
    • Common Issues
    • Debug Mode
    • Links

    Documentation

    Analytical MCP Server

    Model Context Protocol server providing statistical analysis, decision support, logical reasoning, and research verification tools for Claude.

    Setup

    Prerequisites

    • Node.js >= 20.0.0
    • EXA_API_KEY environment variable (for research features)

    Installation

    Option 1: Direct Installation

    bash
    npm install
    npm run build

    Option 2: Docker

    bash
    # Build the Docker image
    docker build -t analytical-mcp .
    
    # Run with environment variables
    docker run -d \
      --name analytical-mcp \
      -e EXA_API_KEY=your_api_key_here \
      -v $(pwd)/cache:/app/cache \
      analytical-mcp
    
    # Or use docker-compose
    cp .env.example .env
    # Edit .env with your API key
    docker-compose up -d

    Configuration

    Direct Installation Configuration

    1. Copy .env.example to .env

    2. Add your EXA_API_KEY to .env

    3. Add to Claude Desktop configuration:

    json
    {
      "mcpServers": {
        "analytical": {
          "command": "node",
          "args": ["/path/to/analytical-mcp/build/index.js"],
          "env": {
            "EXA_API_KEY": "your-exa-api-key-here"
          }
        }
      }
    }

    Docker Configuration

    1. Copy .env.example to .env

    2. Add your EXA_API_KEY to .env

    3. Add to Claude Desktop configuration:

    json
    {
      "mcpServers": {
        "analytical": {
          "command": "docker",
          "args": [
            "run", "--rm", "-i",
            "--env-file", ".env",
            "-v", "$(pwd)/cache:/app/cache",
            "analytical-mcp"
          ]
        }
      }
    }

    Available Tools

    Statistical Analysis

    • **analytical:analyze_dataset** - Statistical analysis of datasets
    • **analytical:advanced_regression_analysis** - Linear, polynomial, and logistic regression
    • **analytical:hypothesis_testing** - Statistical hypothesis testing (t-tests, chi-square, ANOVA)
    • **analytical:data_visualization_generator** - Generate data visualization specifications

    Decision Analysis

    • **analytical:decision_analysis** - Multi-criteria decision analysis with weighted scoring

    Logical Reasoning

    • **analytical:logical_argument_analyzer** - Analyze argument structure and validity
    • **analytical:logical_fallacy_detector** - Detect logical fallacies in text
    • **analytical:perspective_shifter** - Generate alternative perspectives on problems

    Research Verification

    • **analytical:verify_research** - Cross-verify research claims from multiple sources

    Observability & Metrics

    The Analytical MCP Server includes built-in observability features for monitoring circuit breakers and cache performance.

    Metrics Endpoint

    When enabled, the server exposes metrics via HTTP on port 9090 (configurable):

    • **http://localhost:9090/metrics** - Prometheus-style metrics
    • **http://localhost:9090/metrics?format=json** - JSON format metrics
    • **http://localhost:9090/health** - Health check endpoint
    • **http://localhost:9090/** - Metrics server status page

    Available Metrics

    Circuit Breaker Metrics

    • analytical_mcp_circuit_breaker_state - Current state (0=CLOSED, 1=HALF_OPEN, 2=OPEN)
    • analytical_mcp_circuit_breaker_total_calls_total - Total calls through circuit breaker
    • analytical_mcp_circuit_breaker_rejected_calls_total - Rejected calls by circuit breaker
    • analytical_mcp_circuit_breaker_failure_count - Current failure count
    • analytical_mcp_circuit_breaker_success_count - Current success count

    Cache Metrics

    • analytical_mcp_cache_hits_total - Cache hits by namespace
    • analytical_mcp_cache_misses_total - Cache misses by namespace
    • analytical_mcp_cache_puts_total - Cache puts by namespace
    • analytical_mcp_cache_evictions_total - Cache evictions by namespace
    • analytical_mcp_cache_size - Current cache size by namespace

    System Metrics

    • analytical_mcp_uptime_seconds - Server uptime in seconds
    • analytical_mcp_memory_usage_bytes - Memory usage (RSS, heap, external)
    • analytical_mcp_cpu_usage_microseconds - CPU time usage (user, system)

    Configuration

    Enable metrics by setting environment variables:

    bash
    METRICS_ENABLED=true        # Enable metrics server (default: true)
    METRICS_PORT=9090          # Metrics server port (default: 9090)
    METRICS_HOST=127.0.0.1     # Metrics server host (default: 127.0.0.1, use 0.0.0.0 to bind to all interfaces)

    Usage Examples

    bash
    # Get Prometheus metrics
    curl http://localhost:9090/metrics
    
    # Get JSON metrics
    curl http://localhost:9090/metrics?format=json
    
    # Health check
    curl http://localhost:9090/health

    Usage Examples

    Dataset Analysis

    javascript
    {
      "data": [23, 45, 67, 12, 89, 34, 56, 78],
      "analysisType": "stats"
    }

    Decision Analysis

    javascript
    {
      "options": ["Option A", "Option B", "Option C"],
      "criteria": ["Cost", "Quality", "Speed"],
      "weights": [0.4, 0.4, 0.2]
    }

    Logical Analysis

    javascript
    {
      "argument": "All birds can fly. Penguins are birds. Therefore, penguins can fly.",
      "analysisDepth": "comprehensive"
    }

    Development

    Testing

    bash
    # Run all tests
    ./tools/test-runner.sh
    
    # Run specific test suite
    ./tools/test-runner.sh integration
    
    # Available test suites: api-keys, server, integration, research, data-pipeline

    Scripts

    • npm run build - Build TypeScript to JavaScript
    • npm run watch - Watch for changes and rebuild
    • npm run test - Run Jest tests
    • npm run inspector - Start MCP inspector for debugging

    Project Structure

    code
    analytical-mcp/
    ├── src/
    │   ├── tools/           # MCP tool implementations
    │   ├── utils/           # Utility functions
    │   └── index.ts         # Main server entry point
    ├── docs/                # Documentation
    ├── tools/               # Development and testing scripts
    └── examples/            # Usage examples

    Tool Categories

    Statistical Analysis

    • Descriptive statistics: mean, median, standard deviation, quartiles
    • Correlation analysis
    • Regression analysis: linear, polynomial, logistic
    • Hypothesis testing: t-tests, chi-square, ANOVA

    Decision Support

    • Multi-criteria decision analysis
    • Weighted scoring
    • Trade-off analysis
    • Risk assessment

    Logical Reasoning

    • Argument structure analysis
    • Fallacy detection
    • Perspective generation
    • Critical analysis

    Research Integration

    • Multi-source verification
    • Fact extraction
    • Consistency checking
    • Confidence scoring

    Security and Privacy

    • All processing occurs locally
    • Research features use Exa API (optional, requires API key)
    • No permanent data storage
    • Optional file-based caching stored locally only
    • API keys managed via environment variables

    License

    MIT License. See LICENSE file for details.

    Contributing

    1. Fork the repository

    2. Create feature branch: git checkout -b feature/your-feature

    3. Make changes and commit: git commit -m 'Add feature description'

    4. Push to branch: git push origin feature/your-feature

    5. Open pull request

    See docs/DEVELOPMENT.md for detailed development guidelines, code standards, and testing requirements.

    Troubleshooting

    Common Issues

    JSON parsing errors: All logging must go to stderr, not stdout. MCP protocol uses stdout for communication. Use the Logger class, not console.log.

    Tools not appearing: Verify server configuration in Claude Desktop settings and restart Claude Desktop application.

    Research features disabled: Set EXA_API_KEY in your environment or .env file.

    Server not starting: Check Node.js version is 20 or higher and all dependencies are installed with npm install.

    See docs/TROUBLESHOOTING.md for detailed troubleshooting guidance.

    Debug Mode

    Start the server with the MCP inspector:

    bash
    npm run inspector

    Links

    • Model Context Protocol Documentation
    • Exa API Documentation
    • Claude Desktop

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