Can I search for books by William Shakespeare?

Yes! Use the `search_author` tool with the name 'Shakespeare'. It will return a list of his famous plays and sonnets available on Project Gutenberg.

How do I find books about a specific subject like 'History'?

Use the `search_books` tool and include the subject in your query. Your agent will search the entire catalog for titles matching that theme.

Can I get the full text of a book directly?

The current server focuses on metadata and discovery. You can retrieve the official Project Gutenberg ID for any book, which can be used to find the full text on their website.

Project Gutenberg MCP Server for Pydantic AI 3 tools — connect in under 2 minutes

Name: Project Gutenberg
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 3 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Project Gutenberg through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Project Gutenberg "
            "(3 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Project Gutenberg?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Project Gutenberg MCP Server

Equip your AI agent with the largest library of free public domain books through the Project Gutenberg MCP server. This integration provides access to over 60,000 eBooks, allowing your agent to search for classic literature, retrieve detailed metadata for specific titles, and explore works by your favorite authors. Whether you're conducting literary research, looking for historical texts, or simply seeking a new read, your agent acts as a dedicated digital librarian through natural conversation.

Pydantic AI validates every Project Gutenberg tool response against typed schemas, catching data inconsistencies at build time. Connect 3 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Book Search — Find classic books by title, keyword, or subject across a massive collection.
Author Exploration — List all available works by a specific author registered in the database.
Metadata Retrieval — Fetch IDs, languages, and detailed info for any book in the collection.
Literary Auditing — Summarize multiple classic works to compare themes and historical contexts.

The Project Gutenberg MCP Server exposes 3 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Project Gutenberg to Pydantic AI via MCP

Follow these steps to integrate the Project Gutenberg MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 3 tools from Project Gutenberg with type-safe schemas

Why Use Pydantic AI with the Project Gutenberg MCP Server

Pydantic AI provides unique advantages when paired with Project Gutenberg through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Project Gutenberg integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Project Gutenberg connection logic from agent behavior for testable, maintainable code

Project Gutenberg + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Project Gutenberg MCP Server delivers measurable value.

Type-safe data pipelines: query Project Gutenberg with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Project Gutenberg tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Project Gutenberg and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Project Gutenberg responses and write comprehensive agent tests

Project Gutenberg MCP Tools for Pydantic AI (3)

These 3 tools become available when you connect Project Gutenberg to Pydantic AI via MCP:

get_book_details

Get details for a specific Gutenberg book

search_author

Search for books by author

search_gutenberg_books

Search for books on Project Gutenberg

Example Prompts for Project Gutenberg in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Project Gutenberg immediately.

"Find the book 'Pride and Prejudice' on Project Gutenberg."

"List all available works by 'Mark Twain'."

"Search for books about 'Philosophy'."

Troubleshooting Project Gutenberg MCP Server with Pydantic AI

Common issues when connecting Project Gutenberg to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Project Gutenberg + Pydantic AI FAQ

Common questions about integrating Project Gutenberg MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Project Gutenberg MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.