Chronulus AI

by chronulusai

111 stars

7.3k downloads

Not rated

GitHub Website

About

Integrates with Chronulus AI's forecasting API to enable time series analysis, prediction generation, and visualization of forecasting data through natural language commands.

Details

Author: chronulusai
GitHub stars: 111
Downloads: 7,297
Categories: Developer Tools, Other, AI, Design, Frontend, Infrastructure, API
Tags: #data-analysis, #research

- Chat with Chronulus AI forecasting and prediction agents.
- Supports installation via pip, Docker, or uvx.
- Requires a Chronulus API key for authentication.
- Integrates with Claude Desktop on macOS and Windows.
- Compatible with third‑party MCP servers (e.g., filesystem, fetch).
- Provides forecast explanations when plotting outputs.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Chronulus AI

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

From the repository

Follow the general instructions here to configure the Claude desktop client.

You can find your Claude config at one of the following locations:

- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json

Then choose one of the following methods that best suits your needs and add it to your claude_desktop_config.json

<details>
<summary>Using pip</summary>

(Option 1) Install release from PyPI

``bash pip install chronulus-mcp


(Option 2) Install from Github

bash 

git clone https://github.com/ChronulusAI/chronulus-mcp.git

cd chronulus-mcp

pip install .


json 

{

  "mcpServers": {

    "chronulus-agents": {

      "command": "python",

      "args": ["-m", "chronulus_mcp"],

      "env": {

        "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>"

      }

    }

  }

}



Note, if you get an error like "MCP chronulus-agents: spawn python ENOENT", 

then you most likely need to provide the absolute path to python. 

For example /Library/Frameworks/Python.framework/Versions/3.11/bin/python3 instead of just python
</details>
<details>

<summary>Using docker</summary>
Here we will build a docker image called 'chronulus-mcp' that we can reuse in our Claude config.
bash 

git clone https://github.com/ChronulusAI/chronulus-mcp.git

cd chronulus-mcp

 docker build . -t 'chronulus-mcp'



In your Claude config, be sure that the final argument matches the name you give to the docker image in the build command.
json 

{

  "mcpServers": {

    "chronulus-agents": {

      "command": "docker",

      "args": ["run", "-i", "--rm", "-e", "CHRONULUS_API_KEY", "chronulus-mcp"],

      "env": {

        "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>"

      }

    }

  }

}



</details>
<details>

<summary>Using uvx</summary>
uvx will pull the latest version of chronulus-mcp from the PyPI registry, install it, and then run it.

json 

{

  "mcpServers": {

    "chronulus-agents": {

      "command": "uvx",

      "args": ["chronulus-mcp"],

      "env": {

        "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>"

      }

    }

  }

}

Note, if you get an error like "MCP chronulus-agents: spawn uvx ENOENT", then you most likely need to either: 1. install uv or 2. Provide the absolute path touvx. For example /Users/username/.local/bin/uvx instead of just uvx`

</details>

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "chronulus ai": {
            "chronulus-mcp": {
                "command": "docker",
                "args": [
                    "build",
                    ".",
                    "-t",
                    "chronulus-mcp"
                ]
            }
        }
    }
}

McpServers

{
    "chronulus-mcp": {
        "command": "docker",
        "args": [
            "build",
            ".",
            "-t",
            "chronulus-mcp"
        ]
    }
}

Chat with Chronulus AI Forecasting & Prediction Agents in Claude

Claude for Desktop is currently available on macOS and Windows.

Follow the general instructionshereto configure the Claude desktop client.

You can find your Claude config at one of the following locations:

- macOS:~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:%APPDATA%\Claude\claude_desktop_config.json

Then choose one of the following methods that best suits your needs and add it to yourclaude_desktop_config.json

git clone https://github.com/ChronulusAI/chronulus-mcp.git cd chronulus-mcp pip install .

{ "mcpServers": { "chronulus-agents": { "command": "python", "args": ["-m", "chronulus_mcp"], "env": { "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>" } } } }

Note, if you get an error like "MCP chronulus-agents: spawn python ENOENT", then you most likely need to provide the absolute path topython. For example/Library/Frameworks/Python.framework/Versions/3.11/bin/python3instead of justpython

Here we will build a docker image called 'chronulus-mcp' that we can reuse in our Claude config.

git clone https://github.com/ChronulusAI/chronulus-mcp.git cd chronulus-mcp docker build . -t 'chronulus-mcp'

In your Claude config, be sure that the final argument matches the name you give to the docker image in the build command.

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

uvxwill pull the latest version ofchronulus-mcpfrom the PyPI registry, install it, and then run it.

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

Note, if you get an error like "MCP chronulus-agents: spawn uvx ENOENT", then you most likely need to either:
- install uvor
- Provide the absolute path touvx. For example/Users/username/.local/bin/uvxinstead of justuvx

Additional Servers (Filesystem, Fetch, etc)

In our demo, we use third-party servers like fetchand filesystem.

For details on installing and configure third-party server, please reference the documentation provided by the server maintainer.

Below is an example of how to configure filesystem and fetch alongside Chronulus in yourclaude_desktop_config.json:

{ "mcpServers": { "chronulus-agents": { "command": "uvx", "args": ["chronulus-mcp"], "env": { "CHRONULUS_API_KEY": "<YOUR_CHRONULUS_API_KEY>" } }, "filesystem": { "command": "npx", "args": [ "-y", "@modelcontextprotocol/server-filesystem", "/path/to/AIWorkspace" ] }, "fetch": { "command": "uvx", "args": ["mcp-server-fetch"] } } }

To streamline your experience using Claude across multiple sets of tools, it is best to add your preferences to under Claude Settings.

You can upgrade your Claude preferences in a couple ways:

- From Claude Desktop:Settings -> General -> Claude Settings -> Profile (tab)
- Fromclaude.ai/settings:Profile (tab)

Preferences are shared across both Claude for Desktop and Claude.ai (the web interface). So your instruction need to work across both experiences.

Below are the preferences we used to achieve the results shown in our demos:

## Tools-Dependent Protocols The following instructions apply only when tools/MCP Servers are accessible. ### Filesystem - Tool Instructions - Do not use 'read_file' or 'read_multiple_files' on binary files (e.g., images, pdfs, docx) . - When working with binary files (e.g., images, pdfs, docx) use 'get_info' instead of 'read_*' tools to inspect a file. ### Chronulus Agents - Tool Instructions - When using Chronulus, prefer to use input field types like TextFromFile, PdfFromFile, and ImageFromFile over scanning the files directly. - When plotting forecasts from Chronulus, always include the Chronulus-provided forecast explanation below the plot and label it as Chronulus Explanation.

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Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Chat with Chronulus AI Forecasting & Prediction Agents in Claude

Additional Servers (Filesystem, Fetch, etc)

Install

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