putio MCP Server Integration

What does “putio” MCP Server do?

The putio MCP Server is a Model Context Protocol (MCP) server designed to facilitate seamless interaction between AI assistants and the put.io cloud storage service. It acts as a bridge, enabling AI-driven workflows to access, manage, and automate tasks such as listing active transfers, adding new downloads via URL or magnet links, canceling transfers, and retrieving browser links for completed downloads. By connecting AI clients to put.io, this server enhances developer workflows related to media management, file automation, and cloud storage operations, allowing for efficient, programmatic access to storage and transfer functions within the put.io ecosystem.

List of Prompts

No prompt templates are explicitly mentioned in the repository or documentation.

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List of Resources

No explicit resource primitives are documented or listed in the repository.

List of Tools

• List active transfers: Allows clients to retrieve the list of currently active transfers on put.io.
• Add new transfers: Enables clients to add new downloads to put.io using a URL or magnet link.
• Cancel existing transfers: Permits the cancellation of ongoing transfers.
• Get browser links for completed transfers: Provides direct browser links for completed downloads, enabling easy access and sharing.

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Use Cases of this MCP Server

• Automated Download Management: Developers can use the server to programmatically add, monitor, and cancel downloads on put.io, automating workflows for media or data ingestion.
• Media Library Integration: Integrate put.io with media server setups, enabling AI assistants to fetch and organize files as they become available.
• Cloud Storage Automation: Enable AI-driven file management, such as cleaning up completed transfers or retrieving download links for downstream processing.
• Remote Download Control: Provide users or agents with the ability to manage downloads from anywhere, improving accessibility and reducing manual intervention.
• Link Sharing Workflows: Quickly generate and share browser-accessible links to files, streamlining collaboration or content distribution.

How to set it up

Windsurf

1. Ensure you have Python 3.x, uvx, and a valid put.io API token.
2. Locate your Windsurf configuration file.
3. Add the putio MCP Server under mcpServers:

   {
     "mcpServers": {
       "putio": {
         "command": "uvx",
         "args": [
           "putio-mcp-server"
         ],
         "env": {
           "PUTIO_TOKEN": "<your-putio-api-token>"
         }
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the server is available in your MCP server list.

Claude

1. Install Python 3.x and uvx.
2. Obtain your put.io API token.
3. Edit claude_desktop_config.json as follows:

   {
     "mcpServers": {
       "putio": {
         "command": "uvx",
         "args": [
           "putio-mcp-server"
         ],
         "env": {
           "PUTIO_TOKEN": "<your-putio-api-token>"
         }
       }
     }
   }
   

4. Restart Claude Desktop.
5. Confirm that “putio” appears as an available MCP server.

Cursor

1. Make sure Python 3.x, uvx, and your put.io API token are set up.
2. Open the configuration UI or file for Cursor.
3. Add the following snippet:

   {
     "mcpServers": {
       "putio": {
         "command": "uvx",
         "args": [
           "putio-mcp-server"
         ],
         "env": {
           "PUTIO_TOKEN": "<your-putio-api-token>"
         }
       }
     }
   }
   

4. Save and restart Cursor.
5. Check for “putio” MCP server connectivity.

Cline

1. Verify you have Python 3.x, uvx, and your put.io API token.
2. Find Cline’s configuration file.
3. Insert:

   {
     "mcpServers": {
       "putio": {
         "command": "uvx",
         "args": [
           "putio-mcp-server"
         ],
         "env": {
           "PUTIO_TOKEN": "<your-putio-api-token>"
         }
       }
     }
   }
   

4. Restart Cline.
5. Confirm the MCP server “putio” is running.

Securing API Keys

Store sensitive credentials such as your put.io API token in the env object of the server configuration, not directly in your codebase. Example:

{
  "mcpServers": {
    "putio": {
      "command": "uvx",
      "args": [
        "putio-mcp-server"
      ],
      "env": {
        "PUTIO_TOKEN": "<your-putio-api-token>"
      }
    }
  }
}

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:

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:

{
  "putio": {
    "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 “putio” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the above, the putio MCP Server offers basic, well-scoped MCP functionality for put.io, but lacks advanced MCP features (prompts, resources, sampling, roots). For straightforward file and transfer automation, it’s suitable. For more complex or context-rich workflows, it may be limited.

Score: 4/10

MCP Score