## Advanced Workflows for LLM-Native Library Management
The integration of a full-featured MCP server enables a wide array of autonomous workflows that fundamentally change how users interact with their ebook collections.
### Semantic Knowledge Base Construction
By using the FTS and snippet retrieval tools, an LLM can act as a researcher across thousands of volumes. If a user asks a cross-disciplinary question, the agent can:
1. Identify relevant books using a combination of metadata and natural language search.
2. Search within those books for specific concepts using FTS.
3. Retrieve and synthesize fragments of text into a coherent answer, citing the specific book IDs and page/chapter references.
### Autonomous Metadata Cleaning and Taxonomy Management
An agent with read-write access can perform "taxonomy normalization." Many libraries suffer from inconsistent tagging (e.g., "Sci-Fi," "Science Fiction," "SF"). The agent can:
1. List all unique tags in the library.
2. Identify synonymous terms using its internal knowledge.
3. Use the `bulk_update_metadata` tool to merge these tags across all affected books, creating a clean and navigable hierarchy.
### Proactive Content Discovery and Alerting
The MCP server can be used by the agent to monitor for "new additions" to the library by watching for new book_ids. When a new book is added, the agent can automatically:
1. Extract a summary.
2. Determine if the content matches any of the user's specific interests (stored in a custom "Interest" column).
3. Generate a brief "briefing" on why the book might be relevant and present it to the user.
## Usage Examples
### Add a "To Read" tag to books 1 and 2
python
await mcp_session.call_tool("bulk_update_metadata", {
"field_name": "tags",
"new_value": "To Read",
"book_ids": [1, 2]
})
### Rename "SciFi" tag to "Science Fiction" globally
python
await mcp_session.call_tool("bulk_update_metadata", {
"field_name": "tags",
"old_value": "SciFi",
"new_value": "Science Fiction"
})
### Remove "Draft" tag from all books
python
await mcp_session.call_tool("bulk_update_metadata", {
"field_name": "tags",
"old_value": "Draft"
})
