Faim Time Series Forecasting

by S-FM

344 downloads

Not rated

GitHub

About

An MCP server for zero-shot time-series forecasting powered by foundation models such as Chronos 2 and TiRex, with support for multivariate and probabilistic forecasts.

Details

Author: S-FM
Downloads: 344
Categories: Other, AI, Productivity

- Exposes two foundation time-series models: Chronos2 and TiRex.
- Offers two MCP tools: list_models and forecast.
- Accepts 1D arrays for single series or 3D arrays for batch inputs.
- Supports point, quantile, and sample forecast outputs.
- Allows custom quantile levels for risk assessment.
- Works with any MCP-compatible AI assistant.

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 Faim Time Series Forecasting

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": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

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": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

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": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

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": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

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": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

From the repository

Install Node.js 20+, npm 10+, and obtain a FAIM API key from faim.it.com. Configure your MCP client to run the server via npx -y @faim-group/mcp or the global faim-mcp command, setting the FAIM_API_KEY environment variable. The server provides two tools: list_models to retrieve available models and forecast to perform time series forecasting with point, quantile, or sample outputs.

`list_models`

List all available forecasting models and their capabilities. Returns information about Chronos2, TiRex, and other available models, including supported output types and features.

`forecast`

Perform time series forecasting using FAIM platform. Supports both point forecasting (single value) and probabilistic forecasting (confidence intervals). Can handle univariate and multivariate time series data. Currently supported models: Chronos2 (default, recommended for multivariate) and TiRex (fast, univariate only).

Claude Desktop / Cursor

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

{
    "mcpServers": {
        "faim time series forecasting": {
            "faim": {
                "command": "npx",
                "args": [
                    "-y",
                    "@faim-group/mcp"
                ],
                "env": {
                    "FAIM_API_KEY": "your-api-key-here"
                }
            }
        }
    }
}

McpServers

{
    "faim": {
        "command": "npx",
        "args": [
            "-y",
            "@faim-group/mcp"
        ],
        "env": {
            "FAIM_API_KEY": "your-api-key-here"
        }
    }
}

FAIM MCP Server

A Model Context Protocol (MCP) server that integrates the FAIM time series forecasting SDK with any MCP-compatible AI assistant, enabling AI-powered forecasting capabilities.

NPM Package: @faim-group/mcp

Overview

This MCP server currently exposes two foundation time-series models from the FAIM API for zero-shot forecasting:
- Chronos2
- TiRex

Key Features

✅ Two MCP Tools:
- list_models: Returns available forecasting models and capabilities
- forecast: Performs point and probabilistic time series forecasting

✅ Flexible Input Formats:
- 1D arrays: Single univariate time series
- 3D arrays: batch/sequence/feature format

✅ Probabilistic Forecasting:
- Point forecasts (single value predictions)
- Quantile forecasts (confidence intervals)
- Sample forecasts (distribution samples)
- Custom quantile levels for risk assessment

Installation

Prerequisites

- Node.js 20+
- npm 10+
- FAIM API key: Register at https://faim.it.com/ to get your FAIM_API_KEY

Option 1: Install from npm (Recommended)

Configure your client to use it directly with npx:

{
  "mcpServers": {
    "faim": {
      "command": "npx",
      "args": ["-y", "@faim-group/mcp"],
      "env": {
        "FAIM_API_KEY": "your-api-key-here"
      }
    }
  }
}

No installation required - npx will automatically download and run the latest version.

Alternatively, if you prefer to install globally first:

npm install -g @faim-group/mcp

Then in config:

{
  "mcpServers": {
    "faim": {
      "command": "faim-mcp",
      "env": {
        "FAIM_API_KEY": "your-api-key-here"
      }
    }
  }
}

Option 2: Clone and Build Locally

```bash

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About

Details

Jump to

Setting up with Highlight

From the repository

list_models

forecast

Claude Desktop / Cursor

McpServers

FAIM MCP Server

Overview

Key Features

Installation

Prerequisites

Option 1: Install from npm (Recommended)

Option 2: Clone and Build Locally

Install

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`list_models`

`forecast`