# ChronulusAI/chronulus-mcp [Health: Active]

**Category:** 🧮 Data Science Tools  
**Repository:** https://github.com/ChronulusAI/chronulus-mcp  
**GitHub Stars:** 111  
**Views:** 5  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/chronulusai-chronulus-mcp

## Description
Predict anything with Chronulus AI forecasting and prediction agents.

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `uvx` (confidence: high):

```json
"mcpServers": {
  "chronulus-mcp": {
    "command": "uvx",
    "args": ["chronulus-mcp"],
    "env": {
      "CHRONULUS_API_KEY": ""
    }
  }
}
```

**Requires environment variables:** `CHRONULUS_API_KEY` — the values above are empty placeholders; fill in real credentials before running (see the repository for what each one is for).

## Documentation

## What ChronulusAI/chronulus-mcp MCP server does

ChronulusAI/chronulus-mcp MCP server exposes Chronulus AI forecasting and prediction agents through the Model Context Protocol. Its purpose is to let a supported MCP client, especially Claude Desktop, interact with Chronulus agents during a conversation. The repository description focuses on predicting values and outcomes with Chronulus rather than implementing a forecasting model inside the local process.

It does show usage guidance for Chronulus agent workflows: prefer Chronulus input types such as `TextFromFile`, `PdfFromFile`, and `ImageFromFile` when working with files, and include the forecast explanation supplied by Chronulus when presenting a plot.

## How it works

The server operates as a local MCP process. Claude Desktop starts that process using either the Python module, the `uvx` package runner, or a Docker container. Requests are then handled through the configured Chronulus connection, which requires a Chronulus API key.

The repository’s example configuration registers the server under the name `chronulus-agents`. Python starts it with `python -m chronulus_mcp`; the `uvx` example runs the `chronulus-mcp` package; and the Docker example passes the API key into the container. These are alternative launch methods, not separate Chronulus services.

## Setup and configuration

Install Claude for Desktop first, then add an `mcpServers` entry to its configuration file. The README identifies the macOS path as `~/Library/Application Support/Claude/claude_desktop_config.json` and the Windows path as `%APPDATA%\\Claude\\claude_desktop_config.json`.

The required environment variable is `CHRONULUS_API_KEY`. Replace the placeholder in the example configuration with a valid key before starting Claude Desktop. With uvx, the core configuration has this structure:

```json
{
  "mcpServers": {
    "chronulus-agents": {
      "command": "uvx",
      "args": ["chronulus-mcp"],
      "env": {
        "CHRONULUS_API_KEY": "your-key"
      }
    }
  }
}
```

The package can also be installed from PyPI with `pip install chronulus-mcp`, or from a cloned repository with `pip install .`. For Docker, clone the repository, build an image named `chronulus-mcp`, and run it with standard input enabled while passing `CHRONULUS_API_KEY` into the container.

## Tools and capabilities

ChronulusAI/chronulus-mcp MCP server is intended for conversations involving Chronulus forecasting and prediction agents. Supported workflows described in the README include:

- Sending text, PDF, or image file inputs through the corresponding Chronulus input types.
- Requesting forecasts or predictions from Chronulus agents.
- Using Chronulus-provided forecast explanations when displaying plots.
- Running alongside other MCP servers, such as separately installed filesystem or fetch servers.

## Limitations and notes

The documented client setup targets Claude for Desktop on macOS and Windows. The examples also depend on external software: Python and the package installation path, `uvx`, or Docker, depending on the selected method. If Claude reports `spawn python ENOENT` or `spawn uvx ENOENT`, the README recommends installing the missing executable or configuring its absolute path.

The filesystem and fetch entries shown in the README are third-party servers used alongside ChronulusAI/chronulus-mcp MCP server; they are not included capabilities of this project.

_Full upstream README: https://allmcps.com/mcp/chronulusai-chronulus-mcp/readme_