Analytical MCP Server

A Model Context Protocol (MCP) server that provides statistical analysis, decision-making, and logical reasoning tools.

Setup

Prerequisites

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

Installation

Option 1: Direct Installation

npm install
npm run build

Option 2: Docker

# 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

Copy .env.example to .env
Add your EXA_API_KEY to .env
Add to Claude Desktop configuration:

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

Docker Configuration

Copy .env.example to .env
Add your EXA_API_KEY to .env
Add to Claude Desktop configuration:

{
  "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:

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

# 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

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

Decision Analysis

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

Logical Analysis

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

Development

Testing

# 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

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 systems
Trade-off analysis
Risk assessment

Logical Reasoning

Argument structure analysis
Fallacy detection
Perspective generation
Critical thinking support

Research Integration

Multi-source verification
Fact extraction
Consistency checking
Research validation

Security & Privacy

Processing is done locally
Research features use Exa API (optional)
No data is stored permanently
Configurable caching with local-only storage

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Fork the repository
Create your feature branch (git checkout -b feature/feature-name)
Commit your changes (git commit -m 'Add feature description')
Push to the branch (git push origin feature/feature-name)
Open a Pull Request

For detailed contribution guidelines, see docs/DEVELOPMENT.md.

Troubleshooting

Common Issues

JSON parsing errors: Ensure all logging goes to stderr, not stdout. The MCP protocol uses stdout for communication.

Tools not appearing: Verify the server is properly configured in Claude Desktop and restart the application.

Research features disabled: Check that EXA_API_KEY is set in your environment configuration.

Console output issues: The project uses a Logger class for all output. Utility scripts in the tools/ directory integrate with the Logger system for consistent formatting.

Debug Mode

Start the server with the MCP inspector:

npm run inspector

Links

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

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.

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