How to Use the Grepsr MCP in LlamaIndex

Q: How do I load the Grepsr MCP Server into LlamaIndex?

Use llama-index-tools-mcp to initialize the MCP client. Then convert it to a tool list using totoollistasync() and pass it to your function agent.

Q: Can LlamaIndex trigger a Grepsr crawl on demand?

Yes. The LlamaIndex agent invokes runreport when it detects that the indexed data is stale or missing.

Q: How does LlamaIndex avoid indexing duplicate Grepsr records?

The LlamaIndex agent checks the run IDs from getreporthistory to ensure it only processes new data runs.

Q: Can I filter Grepsr data before LlamaIndex indexes it?

Yes, your agent uses getreportdata to request specific fields and rows, reducing noise before vector ingestion.

Index live web data scraped via Grepsr directly into your LlamaIndex vector stores for hallucination-free RAG.

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Connect Grepsr MCP to LlamaIndex

Create your Vinkius account to connect Grepsr 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 Grepsr with LlamaIndex

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Index Live Web Data Directly into LlamaIndex

`get_latest_data` retrieves the most recent scraped dataset from your Grepsr crawler to update your local indexes. Your LlamaIndex agent parses this JSON payload directly into Document nodes for vector storage. Grounding your queries in real data prevents hallucinations. The agent checks `get_report_details` to verify schema fields before updating the vector index with fresh records.

Query Scraping History with Semantic Search

`get_report_history` feeds the execution log of your crawlers into your RAG pipeline. This MCP Server provides the raw metadata so your LlamaIndex query engine knows exactly when the data was last updated. LlamaIndex indexes these run logs so you can query performance metrics. The agent retrieves exact run times and record counts without parsing raw log files manually.

Verify Grepsr Sources Before Indexing

`list_reports` gives your LlamaIndex agent a directory of available web crawlers in your account. The agent matches user queries to the correct report before fetching data. By calling `get_report_data`, the agent queries specific subsets of scraped records instead of downloading entire datasets. This keeps your vector store updates fast and cost-effective.

Setup guide

Set up Grepsr 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 Grepsr 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 Grepsr tools.",
)
response = await agent.run("List recent Grepsr data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Grepsr. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Grepsr MCP in LlamaIndex

Use `llama-index-tools-mcp` to initialize the MCP client. Then convert it to a tool list using `to_tool_list_async()` and pass it to your function agent.

Yes. The LlamaIndex agent invokes `run_report` when it detects that the indexed data is stale or missing.

The LlamaIndex agent checks the run IDs from `get_report_history` to ensure it only processes new data runs.

Yes, your agent uses `get_report_data` to request specific fields and rows, reducing noise before vector ingestion.

Your scraped datasets are pulled directly from Grepsr's API into your local LlamaIndex memory space. Vinkius hosts the server code in an ephemeral sandbox that never caches or logs your raw payload data.

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