New York Times MCP Server for Pydantic AI 9 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect New York Times through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 New York Times "
"(9 tools)."
),
)
result = await agent.run(
"What tools are available in New York Times?"
)
print(result.data)
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 New York Times MCP Server
Connect the New York Times API to any AI agent and unlock access to over 170 years of journalism — including breaking news, historical archives, best-seller lists, and cultural reviews.
Pydantic AI validates every New York Times tool response against typed schemas, catching data inconsistencies at build time. Connect 9 tools through the 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
- Top Stories — Get the latest top stories for any section (World, Politics, Tech, Sports, etc.)
- Article Search — Search the complete archive from 1851 to the present day with keywords and date filters
- Most Popular — See what readers are emailing, sharing, and viewing the most
- Best-Seller Lists — Retrieve current and historical book best-seller lists
- Movie Reviews — Access thousands of movie reviews and critic summaries
- Section Discovery — List all available sections and topics covered by the NYTimes
The New York Times MCP Server exposes 9 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 New York Times to Pydantic AI via MCP
Follow these steps to integrate the New York Times 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 9 tools from New York Times with type-safe schemas
Why Use Pydantic AI with the New York Times MCP Server
Pydantic AI provides unique advantages when paired with New York Times 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 New York Times integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your New York Times connection logic from agent behavior for testable, maintainable code
New York Times + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the New York Times MCP Server delivers measurable value.
Type-safe data pipelines: query New York Times with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple New York Times tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query New York Times and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock New York Times responses and write comprehensive agent tests
New York Times MCP Tools for Pydantic AI (9)
These 9 tools become available when you connect New York Times to Pydantic AI via MCP:
get_archive
Get all articles for a specific month
get_book_lists
"list_name_encoded" is the list slug (e.g., "hardcover-fiction"). Optional date is YYYY-MM-DD. Get current or historical best-seller lists
get_most_emailed
Period can be 1, 7, or 30 days. Get the most emailed articles for a specific period
get_most_shared
Period can be 1, 7, or 30 days. Get the most shared articles on social media
get_most_viewed
Get the most viewed articles
get_movie_reviews
Optional "query" filters by movie title. Search for movie reviews in the NYTimes archive
get_sections
List all available news sections
get_top_stories
g., home, world, politics, technology, sports). Use get_sections to see available options. Get top stories for a specific section
search_articles
Use "q" for keywords, "begin_date" and "end_date" for date ranges (YYYYMMDD), and "sort" for "newest", "oldest", or "relevance". Search for articles using keywords, date ranges, and sorting
Example Prompts for New York Times in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with New York Times immediately.
"Show me today's top world news."
"What is the #1 Hardcover Fiction book this week?"
"Find movie reviews for 'The Godfather'."
Troubleshooting New York Times MCP Server with Pydantic AI
Common issues when connecting New York Times to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiNew York Times + Pydantic AI FAQ
Common questions about integrating New York Times MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
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Connect New York Times to Pydantic AI
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.