Calibre MCP Server
Connects AI agents to Calibre ebook libraries for searching, reading, and managing digital collections. It supports metadata updates, format conversion, and full-text content searches while providing granular permission controls for library access.
README
Calibre MCP Server
This MCP server bridges the gap between AI agents and your Calibre ebook libraries. It enables agents to interact with your collection as a dynamic knowledge base, allowing them to search, manage, and read your digital libraries. Unlike other MCP servers it can also allow an AI agent to update library metadata and contents if a library's permissions are set to allow it.
Key Features
-
Advanced Search: Query libraries using book metadata or perform full-text content searches.
-
Metadata Management: View and update metadata (titles, authors, tags, ratings, etc.) for any book.
-
Library Maintenance: Add new titles to your collection or remove existing ones.
-
Format Conversion: Leverage Calibre’s powerful conversion engine to switch between ebook formats (e.g., PDF to EPUB) on the fly.
-
Direct Reading: Search and read the text content of a book directly into the agent's context window for analysis, summarization, or Q&A.
-
Granular Permissions: Define strict access controls per library, including read-only modes and field-level write restrictions.
Prerequisites
-
Calibre: Must be installed on the host system. This server utilizes
calibre-debugto execute worker processes. -
Concurrency Note: Calibre does not support concurrent access to a single library. Do not point an agent to a library currently being used by the Calibre desktop application or other processes to avoid database corruption.
Configuration
The server is configured via a JSON file. Since JSON does not support comments, use the structure below as a template.
Example Configuration (config.json)
JSON
{
"libraries": {
"default": {
"path": "d:/ebooks/main_library",
"description": "The primary research library containing technical manuals.",
"default": true,
"permissions": {
"read": ["title", "authors", "tags", "rating", "comments"],
"write": ["tags", "rating", "comments"],
"delete": false,
"convert": true
},
"import": {
"allowed_paths": ["d:/downloads/ebook_imports"],
"allow_delete_source": false
},
"export": {
"allowed_paths": ["d:/ebook_exports"s],
"allow_overwrite_destination": false
}
}
},
"port": 8000,
"enable_worker_logging": false,
"expose_resources_via_tools": true,
"log_level": "warning"
}
Configuration Schema Reference
Each library is identified by a unique text key and can have its own separate configuration values:
| Key | Description |
|---|---|
path |
Absolute path to the Calibre library (where metadata.db resides). |
description |
Free-form context provided to the agent explaining what this library contains or what its purpose is. |
default |
If true, the agent uses this library if no specific library is targeted. If you only configure one library then this is unnecessary. |
permissions.read |
Set to true (all fields exposed), false (for a write-only library, if you need one), or a list of specific fields (e.g., ["title", "authors"]). |
permissions.write |
List of metadata fields the agent is allowed to modify, true for all fields and false for a read-only library. |
permissions.delete |
Boolean. If false, the agent cannot delete books from the library. |
permissions.convert |
Boolean. Allows the agent to add new formats to a book record by converting existing ones. If false the server can still convert books for internal use or export, but it won't add the converted files to library book records. |
import.allowed_paths |
A whitelist of directories from which the agent can import new files. |
import.allow_delete_source |
If true, the server can delete the original file after a successful import. |
export.allowed_paths |
A whitelist of directories the agent can export book files to. |
export.allow_overwrite_destination |
If true, the server can overwrite files in the allowed export paths when it exports files there. |
There are also several top-level configuration settings that apply to the MCP server as a whole:
| Key | Description |
|---|---|
port |
The port the server is exposed on. |
enable_worker_logging |
Each Calibre library has its own calibre-debug process that runs code to intereact with the internal Calibre API. When true these processes will write logs to the logs folder for debugging purposes. |
log_level |
Sets what minimum level of logging message will be recorded in logs/app.log. Set to "error", "warning", "info", "debug" or "none". |
expose_resources_via_tools |
Some older MCP clients don't understand the "resources" type that this server exposes, for example to allow the agent to read the contents of the /skills folder. When this setting is true those resources will be exposed via list_help_topics and get_help_topic instead. The libraries resource listing the available libraries and their permissions will also be converted into a list_libraries tool. |
Example MCP Configuration
Point to the above configuration file with the CALIBREMCP_CONFIGPATH environment variable in your MCP configuration. For example:
JSON
{
"mcpServers": {
"calibre": {
"command": "python",
"args": [
"<full path>/calibre_full_mcp/src/server.py"
],
"env": {
"PYTHONPATH": "<full path>/calibre_full_mcp/src",
"CALIBREMCP_CONFIGPATH": "<full path>/calibre_full_mcp/config.json"
}
}
}
}
This should allow you to easily switch library configurations as needed for different agents by selecting which configuration to point CALIBREMCP_CONFIGPATH at.
Pro-Tips for Better Performance
1. Optimize Field Access
Calibre libraries often contain internal metadata that can clutter an agent's context window. It is highly recommended to use a specific list for read permissions. Only expose fields the agent actually needs (e.g., title, author, tags, comments).
2. Custom Fields & Series
-
Custom Fields: If you use custom columns in Calibre, you must include the
#prefix (e.g.,#my_custom_field). -
Series: Every
seriesfield has a correspondingseries_index. Ensure both are included in your permissions list if you want the agent to see or manage book order within a series. -
Descriptions: The server passes custom field "descriptions" to the agent. Use these in Calibre to give the agent hints on how to use specific custom columns. For example if you create a custom field for a book's "age rating"" you could use the description to explain what the values of that field represent.
3. Resource Exposure
If your agent does not yet support the @mcp.resources standard, set expose_resources_via_tools to true. This will expose dedicated tools that allow the agent to fetch files via standard tool calls.
Architecture
For a deep dive into how this server manages worker processes and interacts with the Calibre database, please refer to the Architecture Documentation.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.