Quantitativeresearch

🚀 Quantitative Research MCP Server Usage Instructions

This MCP server is designed specifically for quantitative researchers, offering the following core features:

• Maintain analysis continuity: Track analyses and results across multiple research sessions.
• Organize statistical evidence: Associate hypotheses with supporting statistical tests and results.
• Record variable relationships: Document correlations, predictability, or influence among variables.
• Track model development: Document the evolution of statistical models and their performance.
• Support result interpretation: Connect statistical findings to research questions and theoretical frameworks.
• Ensure methodological rigor: Document methodological decisions and analysis methods.
• Prepare research reports: Organize statistical evidence to support research findings.
• Track research progress: Monitor the status of entities throughout the research lifecycle.
• Prioritize research tasks: Identify and focus on high - priority research activities.
• Plan research process sequence: Plan and visualize the logical sequence of research and analysis steps.

📦 Installation and Configuration

Using Claude Desktop

Add the following content to claude_desktop_config.json:

Install from GitHub and run via npx

{
  "mcpServers": {
    "quantitativeresearch": {
      "command": "npx",
      "args": [
        "-y",
        "github:tejpalvirk/quantitativeresearch"
      ]
    }
  }
}

Install globally and run directly

First, install the package globally:

npm install -g github:tejpalvirk/quantitativeresearch

Then, configure Claude Desktop:

{
  "mcpServers": {
    "quantitativeresearch": {
      "command": "contextmanager - quantitativeresearch"
    }
  }
}

Using Docker

{
  "mcpServers": {
    "quantitativeresearch": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "mcp/quantitativeresearch"
      ]
    }
  }
}

Building from Source

# Clone the repository
git clone https://github.com/tejpalvirk/contextmanager.git
cd contextmanager

# Install dependencies
npm install

# Build the server
npm run build

# Run the server
cd quantitativeresearch
node quantitativeresearch_index.js

Building with Docker

docker build -t mcp/quantitativeresearch -f quantitativeresearch/Dockerfile .

📄 License

This MCP server is released under the MIT License. This means you can freely use, modify, and distribute the software, but you must comply with the terms and conditions of the MIT License. For more detailed information, please refer to the LICENSE file in the project repository.

Environment Variables

The Quantitative Research MCP server supports the following environment variables to customize the data storage location:

• MEMORY_FILE_PATH: The path where the knowledge graph data is stored.

  • It can be an absolute path or a relative path (relative to the current working directory).
  • Default value: ./quantitativeresearch/memory.json

• SESSIONS_FILE_PATH: The path where the session data is stored.

  • It can be an absolute path or a relative path (relative to the current working directory).
  • Default value: ./quantitativeresearch/sessions.json

Example usage:

# Store data at the current location
MEMORY_FILE_PATH="./quantitative - memory.json" SESSIONS_FILE_PATH="./quantitative - sessions.json" 

# Specify the data storage location using an absolute path
MEMORY_FILE_PATH="/path/to/memory.json" SESSIONS_FILE_PATH="/path/to/sessions.json"

# Use a relative path based on the current working directory
MEMORY_FILE_PATH="relative/path/to/memory.json" SESSIONS_FILE_PATH="relative/path/to/sessions.json"

💻 Usage Examples

Basic Usage

# Display help information
quantitativeresearch --help

# Display the version number
quantitativeresearch --version

# Start the server
quantitativeresearch start [--port PORT]

# Stop the server
quantitativeresearch stop

# Restart the server
quantitativeresearch restart

Advanced Usage

Data Storage

# Store a single data point
quantitativeresearch store <key> <value>

# Store data in batches
quantitativeresearch store - batch <key1>=<value1>,<key2>=<value2>...

# Get the data value
quantitativeresearch get <key>

# Delete a data entry
quantitativeresearch delete <key>

Data Analysis

# Perform basic statistical calculations
quantitativeresearch analyze stats [--mean] [--median] [--stddev]

# Generate a data report
quantitativeresearch report generate [--summary] [--detailed]

Data Visualization

# Generate a chart
quantitativeresearch visualize plot <key> [--chart - type LINE/BAR/PIE]

# Display a chart
quantitativeresearch visualize show <key>

Example Usage

# Store data
quantitativeresearch store age=30 name=Alice
quantitativeresearch store - batch height=170,weight=60,BMI=21.5

# Get and display analysis results
quantitativeresearch analyze stats --mean
quantitativeresearch report generate --summary

# Visualize data
quantitativeresearch visualize plot age --chart - type LINE
quantitativeresearch visualize show height

Error Handling

Common Issues

• Port occupied: If the default port (3000) is occupied by another program, the server cannot start. Please ensure that the port is not in use, or specify a different port when starting the server.

  quantitativeresearch start --port 3001
  

• Data format error: When storing data, if the key - value pair format is incorrect, an error will be thrown. Please ensure that the key and value are separated by an equal sign and there are no extra spaces.

  # Incorrect example
  quantitativeresearch store key= value 错误
  
  # Correct example
  quantitativeresearch store key=value
  

• Data not found: When trying to get or delete a non - existent key, an error message will be returned.

  quantitativeresearch get non_existent_key
  # Output: Error: The specified key 'non_existent_key' does not exist
  

Exiting and Debugging

Safe Exit

To safely shut down the server, use the stop command:

quantitativeresearch stop

This will ensure that all unfinished operations are properly handled and all resources are released.

Debug Mode

When encountering problems, you can enable debug mode to get more detailed information:

quantitativeresearch --debug start

This will output detailed debug information in the console to help diagnose potential problems.