Chronulus MCP Server

AI MCP Forecasting Prediction

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What does “Chronulus” MCP Server do?

The Chronulus MCP Server acts as a middleware platform that connects AI assistants—such as forecasting and prediction agents—with external data sources and services. Its primary purpose is to enhance AI-driven workflows for forecasting and predictive analytics by enabling seamless integration with Chronulus AI’s proprietary systems. Through this server, AI clients can perform tasks like querying prediction models, retrieving forecasting data, and managing agent interactions, all in real-time. By exposing standardized interfaces for communication, Chronulus MCP enables developers to leverage advanced AI tools within their development environments, streamlining workflows that require complex data analysis, time series forecasting, and predictive modeling.

List of Prompts

No prompt templates are mentioned in the repository or documentation.

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List of Resources

No explicit resources are listed in the repository or documentation.

List of Tools

No specific tools are listed in the available documentation or in the repository structure. The server.py file is not present or not accessible from the available information.

Use Cases of this MCP Server

  • Forecasting and Prediction: Connect AI agents to Chronulus forecasting models for real-time predictions, helping developers and analysts automate and streamline their forecasting workflows.
  • Integration with Claude Desktop: Easily add advanced prediction capabilities within Claude’s desktop client, enabling direct access to Chronulus agents from popular AI workspaces.
  • Dockerized Deployment: Rapidly deploy forecasting services across environments using Docker, improving portability and scalability for enterprise and research use cases.
  • API Key Management: Securely manage and rotate Chronulus API keys for safe and compliant access to prediction services, supporting organizational security policies.

How to set it up

Windsurf

No Windsurf-specific setup instructions are provided in the repository or documentation.

Claude

  1. Prerequisites: Ensure Python is installed and obtain a Chronulus API key.
  2. Locate Configuration File: Find your Claude config at:
    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  3. Install Chronulus MCP:
    • Via PyPI:
      pip install chronulus-mcp
    • Or from GitHub:
      git clone https://github.com/ChronulusAI/chronulus-mcp.git
      cd chronulus-mcp
      pip install .
      
  4. Edit Config File: Add the MCP server to claude_desktop_config.json:
    {
      "mcpServers": {
        "chronulus-agents": {
          "command": "python",
          "args": ["-m", "chronulus_mcp"],
          "env": {
            "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>"
          }
        }
      }
    }
    
  5. Verify Setup: Restart Claude and ensure the Chronulus server appears as available.

Docker Setup Example:

{
  "mcpServers": {
    "chronulus-agents": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-e", "CHRONULUS_API_KEY", "chronulus-mcp"],
      "env": {
        "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>"
      }
    }
  }
}

UVX Setup Example:

{
  "mcpServers": {
    "chronulus-agents": {
      "command": "uvx",
      "args": ["chronulus-mcp"],
      "env": {
        "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>"
      }
    }
  }
}

Securing API Keys:
Always use environment variables for keys, as shown in the env JSON above.

Cursor

No Cursor-specific setup instructions are provided in the repository or documentation.

Cline

No Cline-specific setup instructions are provided in the repository or documentation.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

FlowHunt MCP flow

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "chronulus-agents": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “chronulus-agents” to the actual name of your MCP server and replace the URL with your own MCP server URL.


Overview

SectionAvailabilityDetails/Notes
OverviewIntro, use, and concept explained
List of PromptsNo prompt templates found
List of ResourcesNo explicit resources listed
List of ToolsNo tool list available
Securing API KeysExample JSON for environment variable usage
Sampling Support (less important in evaluation)No info on sampling support

Between the available sections and missing technical details, Chronulus MCP provides clear setup and security guidance but lacks documented prompt, resource, and tool definitions. Its focus is on integration, not deep customization.

MCP Score

Has a LICENSE✅ (MIT)
Has at least one tool
Number of Forks8
Number of Stars73

Our opinion

Chronulus MCP Server offers a straightforward integration path for forecasting agents and provides robust setup instructions, but the lack of details about prompts, resources, and tools in the documentation limits its extensibility and transparency. Based on the two tables above, we would rate this MCP a 5/10 for general usability and ecosystem maturity.

Frequently asked questions

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