Rijksmuseum MCP Server Integration

What does “Rijksmuseum” MCP Server do?

The Rijksmuseum MCP Server is a Model Context Protocol (MCP) server that provides AI assistants with access to the Rijksmuseum’s vast art collection through natural language interactions. By connecting AI models to external data sources, this server enables exploration, analysis, and interaction with artworks and collections in the Rijksmuseum. It empowers developers and AI agents to perform tasks such as searching for artworks by artist, style, period, or material, retrieving detailed artwork information, accessing high-resolution images, exploring user-curated collections, and analyzing artist timelines. This integration enhances development workflows for cultural, educational, and analytical applications, making it easier for AI tools and users to engage deeply with one of the world’s most renowned art collections.

List of Prompts

No explicit prompt templates are described in the repository files or documentation.

List of Resources

No explicit MCP “resource” primitives are detailed in the available documentation.

List of Tools

• search_artwork: Search and filter Rijksmuseum artworks using text, artist, type, materials, period, colors, and more criteria.
• get_artwork_details: Retrieve comprehensive details about a specific artwork, including title, artist, physical properties, historical context, visuals, curatorial info, and exhibition history.
• get_artwork_image: Access high-resolution images of artworks with deep zoom, tile-based loading, and full resolution support.
• get_user_sets: Browse curated user collections and thematic groupings within the Rijksmuseum collection.
• get_user_set_details: Access detailed information about specific user-created sets or collections.
• open_image_in_browser: Open artwork images directly in a web browser for close inspection and study.
• get_artist_timeline: Generate a chronological timeline of an artist’s works, enabling analysis of career progression, styles, and periods.

Use Cases of this MCP Server

• Artwork Discovery: Easily find paintings or objects by a specific artist, from a specific time period, or matching certain visual features (e.g., “Show me all paintings by Rembrandt from the 1640s”).
• In-depth Artwork Analysis: Retrieve extensive details about a particular artwork, including its history, materials, and exhibition record—supporting research and educational tasks.
• High-Resolution Image Access: Obtain and examine high-definition images of artworks for study, restoration planning, or digital archiving.
• User Collection Exploration: Analyze patterns and themes in user-curated sets, supporting social and collaborative art discovery or educational projects.
• Artist Timeline Analysis: Visualize and study an artist’s evolution, tracking their styles, techniques, and periods for scholarly or curatorial purposes.

How to set it up

Windsurf

1. Ensure Node.js and npm are installed on your machine.
2. Locate your Windsurf configuration file (usually windsurf.config.json).
3. Add the Rijksmuseum MCP Server to the mcpServers section:

   {
     "mcpServers": {
       "rijksmuseum": {
         "command": "npx",
         "args": ["@rijksmuseum/mcp-server@latest"]
       }
     }
   }
   

4. Save the configuration file and restart Windsurf.
5. Verify connection by checking available MCP tools in the Windsurf interface.

Securing API keys:

{
  "mcpServers": {
    "rijksmuseum": {
      "command": "npx",
      "args": ["@rijksmuseum/mcp-server@latest"],
      "env": {
        "RIJKSMUSEUM_API_KEY": "your-api-key-here"
      },
      "inputs": {
        "apiKey": {
          "env": "RIJKSMUSEUM_API_KEY"
        }
      }
    }
  }
}

Claude

1. Make sure Claude supports custom MCP servers (check documentation).
2. Find the configuration section for MCP servers.
3. Add the Rijksmuseum MCP Server configuration:

   {
     "mcpServers": {
       "rijksmuseum": {
         "command": "npx",
         "args": ["@rijksmuseum/mcp-server@latest"]
       }
     }
   }
   

4. Save and reload Claude.
5. Test by querying Rijksmuseum data via Claude’s interface.

Cursor

1. Install Node.js if not present.
2. Open cursor.config.json (or similar MCP config file).
3. Add the Rijksmuseum MCP server:

   {
     "mcpServers": {
       "rijksmuseum": {
         "command": "npx",
         "args": ["@rijksmuseum/mcp-server@latest"]
       }
     }
   }
   

4. Save the file, restart Cursor.
5. Confirm MCP tools appear as available options.

Cline

1. Prerequisite: Node.js environment ready.
2. Go to the Cline configuration file (e.g., cline.config.json).
3. Insert the MCP server block:

   {
     "mcpServers": {
       "rijksmuseum": {
         "command": "npx",
         "args": ["@rijksmuseum/mcp-server@latest"]
       }
     }
   }
   

4. Restart the Cline service.
5. Check for successful connection to the Rijksmuseum MCP server.

Note:
Always secure sensitive API keys using environment variables rather than hardcoding them. Reference them in the config’s env and inputs sections as shown above.

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:

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

Overview

| Roots Support | ⛔ | Not mentioned |

Our opinion

The Rijksmuseum MCP Server offers robust tools for art exploration and analysis, but lacks explicit prompt templates, resource definitions, and documentation on sampling or roots support. It is well-suited for art, culture, and education use cases, but would benefit from clearer prompt and resource documentation for LLM workflows.

MCP Score

Rating:
Based on the tables, I would rate this MCP server a 6/10. It is strong in tooling and has a clear license and moderate community attention, but lacks prompt/resource documentation and clarity on sampling/roots support.