Project Gutenberg MCP Server for OpenAI Agents SDK 3 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Project Gutenberg through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Project Gutenberg Assistant",
instructions=(
"You help users interact with Project Gutenberg. "
"You have access to 3 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Project Gutenberg"
)
print(result.final_output)
asyncio.run(main())
* 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.
The OpenAI Agents SDK auto-discovers all 3 tools from Project Gutenberg through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Project Gutenberg, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the Project Gutenberg MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 3 tools from Project Gutenberg
Why Use OpenAI Agents SDK with the Project Gutenberg MCP Server
OpenAI Agents SDK provides unique advantages when paired with Project Gutenberg through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Project Gutenberg + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Project Gutenberg MCP Server delivers measurable value.
Automated workflows: build agents that query Project Gutenberg, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Project Gutenberg, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Project Gutenberg tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Project Gutenberg to resolve tickets, look up records, and update statuses without human intervention
Project Gutenberg MCP Tools for OpenAI Agents SDK (3)
These 3 tools become available when you connect Project Gutenberg to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting Project Gutenberg to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Project Gutenberg + OpenAI Agents SDK FAQ
Common questions about integrating Project Gutenberg MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Project Gutenberg with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Project Gutenberg to OpenAI Agents SDK
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.
