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Live 25 Actions

Open Library MCP Server
for AI Agents

Connect your AI agent to StackOne's Open Library MCP server and give it 25 MCP tools out of the box. Auth, tool execution, and security all managed.

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Open Library MCP Server
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Coverage

25 Agent Actions

Create, read, update, and delete across Open Library — and extend your agent's capabilities with custom actions.

MCP Actions → Build Actions →

Authentication

Agent Tool Authentication

Per-user OAuth in one call. Your Open Library MCP server gets session-scoped tokens with zero credentials stored on your infra.

Agent Auth →

Security

Agent Protection

Every Open Library tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.

Prompt Injection Defense →

Performance

Max Agent Context. Min Cost.

Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Open Library call.

Tools Discovery →

What is the Open Library MCP Server?

A Open Library MCP server lets AI agents read and write Open Library data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Open Library MCP server ships with 25 pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.

All Open Library MCP Tools

Every action from Open Library's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.

Authors

  • Search Authors

    Search authors by name in the Open Library catalog

  • Get Author

    Get an author record by their Open Library author ID

Editions

  • Get Edition

    Get a book edition record by its Open Library edition ID

  • List List Editions

    List the book editions collected by a reading list

Seeds

  • List List Seeds

    List the seeds (books, works, authors, or subjects) in a reading list

  • Update List Seeds

    Add or remove seeds on a reading list of the connected Open Library account

Subjects

  • Search Subjects

    Search subjects by name in the Open Library catalog

  • Get Subject

    List works tagged with a subject

Other (17)

  • Create List

    Create a reading list on the connected Open Library account

  • List Reading Log

    List the books on a reader's shelf (want to read, currently reading, or already read)

  • List Recent Changes

    List recent edits made across the Open Library catalog

  • List Author Works

    List the works written by an author

  • Search Books

    Search books, works, and authors across the Open Library catalog

  • Get Work

    Get a work record by its Open Library work ID

  • List Work Editions

    List the editions published for a work

  • Get Edition By ISBN

    Get a specific book edition by its ISBN-10 or ISBN-13

  • Get Work Ratings

    Get the community rating summary for a work

  • Get Work Bookshelves

    Get reading-log counts for a work (want to read, currently reading, already read)

  • Search Inside Books

    Full-text search across the scanned contents of books

  • Get Volume

    Get a brief bibliographic record by identifier type and value

  • Search Lists

    Search reader-curated lists by keyword

  • List User Lists

    List the reading lists created by an Open Library user

  • Get List

    Get a reading list by its owner and list ID

  • Get Lists Containing Seed

    List the public reading lists that contain a given work, edition, or author

  • Delete List

    Delete a reading list from the connected Open Library account

Set Up Your Open Library MCP Server in Minutes

One endpoint. Any framework. Your agent is talking to Open Library in under 10 lines of code.

MCP Clients

Claude Desktop setup guide
Claude Code setup guide
Cursor setup guide
Goose setup guide

Agent Frameworks

Claude Desktop
{
  "mcpServers": {
    "stackone": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote@latest",
        "https://api.stackone.com/mcp?x-account-id=<account_id>",
        "--header",
        "Authorization: Basic <YOUR_BASE64_TOKEN>"
      ]
    }
  }
}

Platform Resources

MCP Code Mode: Keeping Tool Responses Out of Agent Context

Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.

11 min

Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery

Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.

10 min

Indirect Prompt Injection Defense for MCP Tools: A Technical Guide

MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.

12 min

MCP vs A2A: Architecture, Security, and When to Use Each

MCP vs A2A: what each protocol standardizes, how they differ, their shared security risks including indirect prompt injection, and when to use one, both, or a hybrid architecture.

12 min

MCP vs API: What 200+ Connector Builds Taught Us

MCP wraps APIs, it doesn't replace them. After building 200+ connectors that serve both, here's when each approach wins.

14 min read

Open Library MCP Server FAQ

Does StackOne have a Open Library MCP server?
Yes. StackOne offers a hosted Open Library MCP server with 25 pre-built actions, and every action is tested and QA'd by StackOne. Connect it to Claude, Cursor, and any other MCP client, or to any agent framework through the AI Action SDK. It ships with managed agent authentication, prompt injection defense, and tool discovery with server-side execution that preserve your agent's context window and keep reasoning performance.
Open Library MCP server vs direct API integration — what's the difference?
A Open Library MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software — backend code calling Open Library. A Open Library MCP server is for AI agents — MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI — discovering and calling Open Library at runtime. StackOne provides both.
How does Open Library authentication work for AI agents?
Open Library authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK — you get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own Open Library account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via origin_owner_id.
Are Open Library MCP tools vulnerable to prompt injection?
Yes — Open Library MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content — documents, messages, tickets, records, or free-text fields — is a potential vector. StackOne Defender scans every tool response before it enters the agent's context — regex patterns in ~1ms, then a MiniLM classifier in ~4ms. 88.7% accuracy, CPU-only.
What is the context bloat of a Open Library agent and how do I avoid it?
Context bloat happens when Open Library tool schemas and API responses eat your Open Library agent's memory, preventing it from reasoning effectively. A single Open Library query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery and Code Mode reduce context bloat — loading only relevant tools per query and keeping raw responses out of the agent's context.
Can I limit which actions my Open Library agent can access?
Yes — you can limit which actions your Open Library agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my Open Library MCP server?
Yes — you can create custom agent actions for your Open Library MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research Open Library's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a Open Library MCP server?
Skip a Open Library MCP server if your integration is purely software-to-software — direct Open Library API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call Open Library actions at runtime.
What AI frameworks and AI clients does the StackOne Open Library MCP server support?
The StackOne Open Library MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.

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