Olostep MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Check Olostep Status, Create Agent, Create Batch, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Olostep as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Olostep app connector for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Olostep. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Olostep?"
)
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 Olostep MCP Server
Connect your Olostep account to any AI agent and take full control of your web scraping orchestration and automated data extraction workflows through natural conversation.
LlamaIndex agents combine Olostep tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through 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
- Scraping Batch Orchestration — List and manage your entire portfolio of scraping batches programmatically, retrieving detailed technical status and URL counts
- URL Extraction Intelligence — Programmatically trigger and monitor real-time URL scrapes to maintain a perfectly coordinated knowledge pipeline
- Agent & Schedule Architecture — Access your complete directory of research agents and automated schedules to oversee your organizational data ingestion
- Hosted Result Monitoring — Access hosted result URLs (Markdown, JSON) and retrieve technical metadata for your research archive in real-time
- Operational Monitoring — Verify account-level API connectivity and monitor scraping volume directly through your agent for perfectly coordinated service scaling
The Olostep MCP Server exposes 10 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.
All 10 Olostep tools available for LlamaIndex
When LlamaIndex connects to Olostep through Vinkius, your AI agent gets direct access to every tool listed below — spanning headless-browser, data-extraction, web-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify Olostep API connectivity
Create a scraping agent
Pass URLs as comma-separated values. Create a batch scrape
Get agent details
Get batch details
Get batch results
Get API usage stats
List scraping agents
List all batches
Optionally specify format: markdown, html, or text. Scrape a web page
Connect Olostep to LlamaIndex via MCP
Follow these steps to wire Olostep into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Olostep MCP Server
LlamaIndex provides unique advantages when paired with Olostep through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Olostep tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Olostep tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Olostep, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Olostep tools were called, what data was returned, and how it influenced the final answer
Olostep + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Olostep MCP Server delivers measurable value.
Hybrid search: combine Olostep real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Olostep 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 Olostep for fresh data
Analytical workflows: chain Olostep queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Olostep in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Olostep immediately.
"Scrape the homepage of example.com as markdown."
"Create a batch scrape for 5 competitor product pages."
"Show my Olostep API usage this month."
Troubleshooting Olostep MCP Server with LlamaIndex
Common issues when connecting Olostep to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpOlostep + LlamaIndex FAQ
Common questions about integrating Olostep MCP Server with LlamaIndex.