Calibre MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Calibre MCP Server Find all books about machine learning and summarize the first chapter of the top result."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
Related MCP server: calibre-mcp
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 calibre processes to avoid database corruption. Setting a
worker_timeoutcan reduce the risk of this happening accidentally, but don't rely on that to protect your libraries. Be aware of what you're doing.
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
},
"worker_timeout": 300
}
},
"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 |
| Absolute path to the Calibre library (where |
| Free-form context provided to the agent explaining what this library contains or what its purpose is. |
| If |
| Set to |
| List of metadata fields the agent is allowed to modify, |
| Boolean. If |
| Boolean. Allows the agent to add new formats to a book record by converting existing ones. If |
| A whitelist of directories from which the agent can import new files. |
| If |
| A whitelist of directories the agent can export book files to. |
| If |
| An integer in seconds. This specific library's |
There are also several top-level configuration settings that apply to the MCP server as a whole:
Key | Description |
| The port the server is exposed on. |
| Each Calibre library has its own |
| For efficiency, the |
| Sets what minimum level of logging message will be recorded in |
| 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 |
Example MCP Configuration
You can run this MCP server using uvx, which will seamlessly download and run the latest version from GitHub without needing a manual installation.
First, install uv if you haven't already.
Then, point to your configuration file with the CALIBREMCP_CONFIGPATH environment variable in your MCP clients configuration. For example:
JSON
{
"mcpServers": {
"calibre": {
"command": "uvx",
"args": [
"--from",
"github.com/FaceDeer/calibre_full_mcp_server",
"calibre-full-mcp"
],
"env": {
"CALIBREMCP_CONFIGPATH": "<full path to your config.json>"
}
}
}
}(Note: If you have cloned the repository locally and wish to run from your local copy, you can replace "github.com/FaceDeer/calibre_full_mcp_server" with the <full path to your local repository directory>.)
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.
Docker Support
If you are building a Docker image for this server, it is recommended to pre-download the necessary NLTK models during the build phase to avoid runtime downloads and slow startup.
You can use the provided setup script for this purpose:
# Inside your Dockerfile
RUN calibre-full-mcp-setupThis will download the punkt and punkt_tab models into the image.
Architecture
For a deep dive into how this server manages worker processes and interacts with the Calibre database, please refer to the Architecture Documentation.
Available Tools
7 toolsfts_searchC
Full-Text Search for a string. Returns a list of hits that include a book_id and a short snippet of text containing an example of the search string's use in that book.
Inputs: query (required), library_name.
get_book_contentC
Retrieve text content of a book. limit: Maximum number of characters to return (default 30,000). offset: Character offset to start reading from. sentence_aware: If True, adjusts the limit to the nearest sentence boundary.
Inputs: book_id (required), limit, offset, sentence_aware, +1 more.
get_book_detailsC
Get detailed metadata for a book. fields: an optional list of metadata fields to return (e.g. ["title", "rating", "#genre"]). If not provided, returns all fields.
Inputs: book_id (required), fields, library_name.
get_field_valuesA
Get unique values and their counts for a specific metadata field. Useful for building facets (e.g. list of all tags or authors). field_name: The name of the field. book_ids: Optional list of book IDs to restrict the search to. value_filter: Optional regex to filter values. limit: Max number of values to return (default 50). offset: Offset for pagination.
Inputs: field_name, book_ids, value_filter, limit, +2 more.
get_library_schemaB
Get the schema of the library, including standard and custom columns. Useful for understanding available metadata fields for search and update.
Inputs: library_name.
search_book_contentC
Search for text within a book. Returns a list of hits with text snippets. hit_limit: Max number of hits to return (default 10). offset: Offset for pagination of hits.
Inputs: book_id (required), query (required), hit_limit, offset, +1 more.
search_booksA
Search for books matching a metadata query. If query is not provided, lists all books. Supports pagination by the limit and offset parameters: limit determines how many results to show (default 50), offset sets the starting point for the results (default 0). fields: Optional list of metadata fields to return (e.g. ["title", "rating", "#genre"]). Returns all if not provided. text_field_limit: Optional max length for text fields in the returned metadata.
Inputs: query, limit, offset, fields, +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 7 tools
Most tools have distinct purposes, but there is some overlap between 'fts_search' and 'search_book_content', which both search text within books, potentially causing confusion. However, their descriptions clarify that 'fts_search' is for full-text search across the library while 'search_book_content' is for searching within a specific book, which helps mitigate ambiguity.
All tool names follow a consistent snake_case pattern with clear verb_noun structures, such as 'get_book_details', 'search_books', and 'get_field_values'. This predictability makes it easy for agents to understand and use the tools without confusion.
With 7 tools, the server is well-scoped for managing a Calibre library, covering essential operations like searching, retrieving content, and metadata management. Each tool serves a clear purpose without being overly sparse or bloated.
The tool set provides strong coverage for reading and searching a Calibre library, including metadata, content, and schema operations. A minor gap exists in the lack of update or delete tools for books or metadata, but this is reasonable if the server is focused on querying rather than modification.
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