How to Use the Newslit MCP in LlamaIndex

Q: How do I load Newslit data into LlamaIndex?

Use llama-index-tools-mcp to connect to the Vinkius endpoint. This registers the tools directly into your environment so your agent can run live queries.

Q: Can LlamaIndex search through old Newslit reports?

Yes, the engine calls listreports to gather your tracking configurations. It then pulls and indexes individual stories via liststories for semantic retrieval.

Q: Does LlamaIndex support updating Newslit reports?

It does. Your agent uses updatereport to modify existing tracking parameters when new keywords or search terms need to be added.

Index live media coverage and press reports directly into LlamaIndex for semantic search and RAG pipelines.

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Connect Newslit MCP to LlamaIndex

Create your Vinkius account to connect Newslit to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Newslit with LlamaIndex

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Index Newslit MCP Server data for RAG

The `list_stories` tool turns raw press coverage into searchable knowledge for your RAG pipeline. It loads recent news directly into your vector database. When users query your system, it searches actual media hits instead of guessing. You get grounded answers based on real data pulled via `get_report`.

Semantic search over historical media reports

The `list_reports` tool replaces endless spreadsheets by letting LlamaIndex query your tracking configurations using natural language. It searches through past coverage parameters to find matching trends. The framework queries `get_report` to pull specific details and runs semantic comparisons. You find related coverage across different reports without writing complex database queries.

Automated report curation with LlamaIndex agents

The `create_report` tool lets LlamaIndex agents build autonomous systems that manage your media files. The agent uses the MCP Server to run operations based on user queries. If search trends shift, the agent runs `update_report` to change the query criteria. It cleans up stale tracking files using `delete_report` to keep your vector index clean.

Setup guide

Set up Newslit MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Newslit MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Newslit tools.",
)
response = await agent.run("List recent Newslit data")

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Common questions about Newslit MCP in LlamaIndex

Use `llama-index-tools-mcp` to connect to the Vinkius endpoint. This registers the tools directly into your environment so your agent can run live queries.

Yes, the engine calls `list_reports` to gather your tracking configurations. It then pulls and indexes individual stories via `list_stories` for semantic retrieval.

It does. Your agent uses `update_report` to modify existing tracking parameters when new keywords or search terms need to be added.

By feeding the output of the MCP Server directly into the context window. The model answers questions using verified media data instead of training memory.

Your custom reports and monitored keywords are protected by Vinkius's zero-trust gateway. Data retrieved from your news feeds is processed in memory and never stored on external servers.

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