Mcp Workflowy

by danield137

28 stars

190 downloads

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GitHub

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About

Mcp Workflowy is an MCP server that provides a programmatic interface to Workflowy, enabling AI assistants to read and manipulate Workflowy lists. It uses username/password authentication and offers tools for searching, creating, updating, and toggling nodes.

Details

Author: danield137
GitHub stars: 28
Downloads: 190
Categories: Other

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 Mcp Workflowy

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": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

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": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

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": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

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": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

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": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

From the repository

Install globally via npm install -g mcp-workflowy or run directly with npx mcp-workflowy server start. Configure credentials via a .env file with WORKFLOWY_USERNAME and WORKFLOWY_PASSWORD, or set them as environment variables. Then start the server and connect your AI assistant to the MCP server.

`list_nodes`

List nodes in Workflowy. If a `parentId` is provided, it lists the child nodes of that parent. If omitted, it lists the root nodes.

`search_nodes`

Search nodes in Workflowy

`create_node`

Create a new node

`update_node`

Update an existing node

`toggle_complete`

Toggle completion status of a node

Claude Desktop / Cursor

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

{
    "mcpServers": {
        "mcp workflowy": {
            "workflowy": {
                "command": "npx",
                "args": [
                    "-y",
                    "mcp-workflowy@latest",
                    "server",
                    "start"
                ],
                "env": {
                    "WORKFLOWY_USERNAME": "",
                    "WORKFLOWY_PASSWORD": ""
                }
            }
        }
    }
}

McpServers

{
    "workflowy": {
        "command": "npx",
        "args": [
            "-y",
            "mcp-workflowy@latest",
            "server",
            "start"
        ],
        "env": {
            "WORKFLOWY_USERNAME": "",
            "WORKFLOWY_PASSWORD": ""
        }
    }
}

Workflowy MCP

A Model Context Protocol (MCP) server for interacting with Workflowy. This server provides an MCP-compatible interface to Workflowy, allowing AI assistants to interact with your Workflowy lists programmatically.

What is MCP?

The Model Context Protocol (MCP) is a standardized way for AI models to interact with external tools and APIs. This server implements MCP to allow AI assistants (like ChatGPT) to read and manipulate your Workflowy lists through a set of defined tools.

Features

- Workflowy Integration: Connect to your Workflowy account using username/password authentication
- MCP Compatibility: Full support for the Model Context Protocol
- Tool Operations: Search, create, update, and mark nodes as complete/incomplete in your Workflowy

Example Usage:

Personally, I use workflowy as my project management tool. Giving my agent access to my notes, and my code base, the following are useful prompts:

- "Show my all my notes on project XYZ in workflowy"
- "Review the codebase, mark all completed notes as completed"
- "Given my milestones on workflowy for this project, suggest what my next task should be"

Installation

Prerequisites

- Node.js v18 or higher - A Workflowy account

Quick Install

NPM Version
NPM Downloads

# Install the package globally
npm install -g mcp-workflowy
Or use npx to run it directly
npx mcp-workflowy server start

Configuration

Create a .env file in your project directory with the following content:

WORKFLOWY_USERNAME=your_username_here
WORKFLOWY_PASSWORD=your_password_here

Alternatively, you can provide these credentials as environment variables when running the server.

Usage

Starting the Server

# If installed globally
mcp-workflowy server start
Using npx
npx mcp-workflowy server start

Available Tools

This MCP server provides the following tools to interact with your Workflowy:

1. list_nodes - Get a list of nodes from your Workflowy (root nodes or children of a specified node)
2. search_nodes - Search for nodes by query text
3. create_node - Create a new node in your Workflowy
4. update_node - Modify an existing node's text or description
5. toggle_complete - Mark a node as complete or incomplete

Integrating with AI Assistants

To use this MCP server with AI assistants (like ChatGPT):

1. Start the MCP server as described above
2. Connect your AI assistant to the MCP server (refer to your AI assistant's documentation)
3. The AI assistant will now be able to read and manipulate your Workflowy lists

One-Click

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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About

Details

Jump to

Setting up with Highlight

From the repository

list_nodes

search_nodes

create_node

update_node

toggle_complete

Claude Desktop / Cursor

McpServers

Workflowy MCP

What is MCP?

Features

Example Usage:

Installation

Prerequisites

Quick Install

Or use npx to run it directly

Configuration

Usage

Starting the Server

Using npx

Available Tools

Integrating with AI Assistants

One-Click

Contributing

License

Install

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`list_nodes`

`search_nodes`

`create_node`

`update_node`

`toggle_complete`