Goodreads MCP Server
Allows retrieving books from a user's Goodreads library by accessing the user's account with their credentials
Click on "Install 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., "@Goodreads MCP Servershow me my currently reading books"
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.
⚠️ DEPRECATED
This repository has been deprecated and is no longer maintained.
🔄 Migration Notice
Please use the new GetGather MCP instead:
👉 github.com/mcp-getgather/mcp-getgather
All future development, updates, and support will be provided in the new repository.
Thank you for your understanding.
Available Tools
1 toolget_booksB
Get books from Goodreads using configured credentials. Credentials should be set via environment variables GOODREADS_EMAIL, and GOODREADS_PASSWORD.
Returns: Dictionary containing profile_id and list of books
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses credential requirements and the return format, which adds useful behavioral context. However, it lacks details on error handling, rate limits, or other operational traits, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose and moving to setup and returns. Every sentence adds value, though minor improvements in flow could make it slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple retrieval with no parameters) and the presence of an output schema, the description covers basics like purpose and credentials. However, it lacks details on authentication errors or data scope, making it minimally adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since there are 0 parameters and schema description coverage is 100%, the baseline is high. The description appropriately doesn't add unnecessary parameter details, focusing instead on setup and output, which aligns well with the empty input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('books from Goodreads'), making it immediately understandable. However, it doesn't differentiate from sibling tools since there are none, so it can't achieve a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, as it only mentions credential setup without context about scenarios or prerequisites. This lack of usage context limits its helpfulness for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v1.0.0- First observed
get_books
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'get_books' has a clearly defined purpose that cannot be confused with any other tool in the set.
The single tool name follows a clear verb_noun pattern ('get_books'), and with only one tool, there is no inconsistency to evaluate. The naming convention is straightforward and appropriate for the function.
A single tool is too few for a server named 'Goodreads MCP Server', which implies broader functionality for interacting with the Goodreads platform. The scope appears limited to retrieving books only, lacking operations like search, reviews, or user interactions, making the tool count insufficient for the expected domain.
The tool surface is severely incomplete for a Goodreads server. It only provides book retrieval, missing essential operations such as searching books, managing reviews, accessing user profiles, or handling shelves. This creates significant gaps that will likely cause agent failures when attempting typical Goodreads-related tasks.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
- QuallaaOAuthcom.quallaa
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Gutendex MCP — wraps Gutendex API for Project Gutenberg books (free, no auth)
AI Visibility and Content Intelligence tools for Claude and MCP-compatible agents.
Books MCP — wraps Open Library API (free, no auth)
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