MCP Open Library MCP Server

What does “MCP Open Library” MCP Server do?

MCP Open Library is a Model Context Protocol (MCP) server that connects AI assistants with the Internet Archive’s Open Library API. Its primary function is to enable seamless interaction between AI clients and the vast database of books and authors managed by Open Library. By integrating this MCP server, AI tools can search for books by title, query author information, retrieve detailed metadata, and access media like book covers and author photos. This streamlines workflows for developers and assistants working with bibliographic data, supports research and discovery tasks, and allows for programmatic access to structured book and author data without manual API management.

List of Prompts

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

List of Resources

No explicit MCP resources are specified in the available documentation or code.

List of Tools

• get_book_by_title: Search for books in Open Library using their title.
• get_authors_by_name: Search for authors by their name.
• get_author_info: Retrieve detailed author information using their Open Library key.
• get_author_photo: Get the URL for an author’s photo using their Open Library ID (OLID).
• get_book_cover: Retrieve the URL for a book’s cover image using identifiers such as ISBN, OCLC, LCCN, OLID, or ID.
• get_book_by_id: Retrieve detailed book information using identifiers like ISBN, LCCN, OCLC, or OLID.

Use Cases of this MCP Server

• Book Information Lookup: Instantly search for and retrieve structured data about books by title, facilitating bibliographic research or reading list generation.
• Author Discovery: Find authors by name and access their profiles, supporting educational tools, recommendation engines, or library management systems.
• Enriched Metadata Retrieval: Obtain detailed book or author information for cataloging, citation tools, or literary analysis platforms.
• Media Access for Books and Authors: Fetch cover images and author photos to enhance user interfaces, book review sites, or digital libraries.
• Automated Data Integration: Seamlessly pull Open Library data into custom apps, bots, or workflows without direct API management.

How to set it up

Windsurf

1. Ensure Node.js and npm are installed on your system.
2. Locate your Windsurf configuration file.
3. Add MCP Open Library to your mcpServers configuration:

   {
     "mcpServers": {
       "open-library": {
         "command": "npx",
         "args": ["@8enSmith/mcp-open-library@latest"]
       }
     }
   }
   

4. Save your configuration and restart Windsurf.
5. Verify the server connection in your Windsurf dashboard.

Claude

1. Open Smithery (or use npx Smithery CLI).
2. Run:

   npx -y @smithery/cli install @8enSmith/mcp-open-library --client claude
   

3. Confirm installation and ensure @8enSmith/mcp-open-library appears in your Claude MCP configuration.
4. Restart Claude Desktop if necessary.
5. Use the tools via Claude’s interface.

Example JSON:

{
  "mcpServers": {
    "open-library": {
      "command": "npx",
      "args": ["@8enSmith/mcp-open-library@latest"]
    }
  }
}

Cursor

1. Open Cursor and navigate to your settings or plugins configuration.
2. Add the MCP server as follows:

   {
     "mcpServers": {
       "open-library": {
         "command": "npx",
         "args": ["@8enSmith/mcp-open-library@latest"]
       }
     }
   }
   

3. Save settings and reload Cursor.
4. Check that the server is available in your tool list.
5. Test a simple book or author query.

Cline

1. Ensure you have Node.js installed.
2. Edit your Cline configuration file.
3. Insert the following MCP server config:

   {
     "mcpServers": {
       "open-library": {
         "command": "npx",
         "args": ["@8enSmith/mcp-open-library@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Run a test to verify.

Securing API Keys

If API keys are required, secure them via environment variables. Example:

{
  "mcpServers": {
    "open-library": {
      "command": "npx",
      "args": ["@8enSmith/mcp-open-library@latest"],
      "env": {
        "OPEN_LIBRARY_API_KEY": "${OPEN_LIBRARY_API_KEY}"
      },
      "inputs": {
        "apiKey": "${OPEN_LIBRARY_API_KEY}"
      }
    }
  }
}

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:

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

Overview

Our opinion

MCP Open Library provides robust, well-documented tools for bibliographic and metadata queries, but lacks explicit prompt templates and MCP resources. Its setup is typical for MCP servers, and the public MIT license is a plus. Sampling and roots support are not mentioned. Overall, it’s a strong, focused MCP server for book and author data.

MCP Score

MCP Score: 7/10.
Great for book/author search and metadata, but missing advanced MCP features and resource/prompt specification.