How to Use the Octoparse MCP in LlamaIndex

Q: How do I handle authentication for Octoparse in LlamaIndex?

The server manages the gettoken flow. You simply provide your credentials, and the MCP client handles the session lifecycle automatically.

Q: Does LlamaIndex support task parameter updates?

Yes, you can call updatetaskparams to change the scraping targets before you run a new indexing job.

Index your Octoparse web data directly into LlamaIndex for semantic search.

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Connect Octoparse MCP to LlamaIndex

Create your Vinkius account to connect Octoparse 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 Octoparse with LlamaIndex

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Ingest Octoparse data into LlamaIndex

Retrieve scraped records using `get_task_data` and feed them into your vector store. LlamaIndex turns raw API output into a searchable knowledge base. Your agent builds a RAG pipeline where the answers come from live web data. It eliminates hallucinations by grounding responses in actual crawl results.

Real-time crawler status

Keep your index updated by checking `get_task_status` periodically. You can automate your agent to trigger `start_task` whenever the index needs fresh content. This keeps your knowledge base current. You always know exactly when new data is ready for ingestion.

Scoped task execution

Use `list_tasks` to verify which crawlers are running. You can target specific tasks to ensure only relevant information enters your LlamaIndex workflow. This granularity prevents noise in your vectors. You control the data quality by selecting exactly which tasks to pull from.

Setup guide

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

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Common questions about Octoparse MCP in LlamaIndex

You use the MCP tool spec to convert server functions into LlamaIndex tools. This allows your agent to fetch data and index it in one sequence.

Yes, if you store the retrieved data in your vector index. You can then query your historical crawl data using natural language.

The server manages the `get_token` flow. You simply provide your credentials, and the MCP client handles the session lifecycle automatically.

Your scraped information stays within your local index. We only touch the raw text and metadata returned by the API during your specific queries.

Yes, you can call `update_task_params` to change the scraping targets before you run a new indexing job.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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