New York Times MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add New York Times as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to New York Times. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in New York Times?"
)
print(response)
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.
LlamaIndex agents combine New York Times tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the New York Times MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the New York Times MCP Server
LlamaIndex provides unique advantages when paired with New York Times through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine New York Times tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain New York Times tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query New York Times, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what New York Times tools were called, what data was returned, and how it influenced the final answer
New York Times + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the New York Times MCP Server delivers measurable value.
Hybrid search: combine New York Times real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query New York Times to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying New York Times for fresh data
Analytical workflows: chain New York Times queries with LlamaIndex's data connectors to build multi-source analytical reports
New York Times MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect New York Times to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting New York Times to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpNew York Times + LlamaIndex FAQ
Common questions about integrating New York Times MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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Connect New York Times to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.