Apify MCP Server for LlamaIndexGive LlamaIndex instant access to 7 tools to Get Dataset Results, Get Run Details, List Actor Runs, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Apify 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 Apify app connector for LlamaIndex is a standout in the Friends Mcp category — giving your AI agent 7 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 Apify. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Apify?"
)
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 Apify MCP Server
Connect your Apify account to any AI agent and simplify how you manage your web scraping, automation actors, and data storage through natural conversation.
LlamaIndex agents combine Apify tool responses with indexed documents for comprehensive, grounded answers. Connect 7 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
- Actor Control — List and trigger serverless actors for web scraping and automation directly from your agent.
- Dataset Retrieval — Fetch the resulting data records (items) from your datasets to analyze or process values via AI.
- Run Monitoring — Track the history and status of recent actor executions to ensure reliability.
- Task Management — List and query configured actor tasks to reuse saved scraper settings.
- Data Insights — Retrieve detailed metadata and logs for specific runs to debug complex automations.
- Storage Visibility — List all datasets in your account to manage your collected web data.
The Apify MCP Server exposes 7 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 7 Apify tools available for LlamaIndex
When LlamaIndex connects to Apify through Vinkius, your AI agent gets direct access to every tool listed below — spanning data-extraction, serverless-actors, 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.
Get items from a dataset
Get details for a specific run
List recent actor executions
List configured actor tasks
List Apify actors
List Apify datasets
Trigger an actor run
Connect Apify to LlamaIndex via MCP
Follow these steps to wire Apify 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 Apify MCP Server
LlamaIndex provides unique advantages when paired with Apify through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Apify tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Apify tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Apify, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Apify tools were called, what data was returned, and how it influenced the final answer
Apify + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Apify MCP Server delivers measurable value.
Hybrid search: combine Apify real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Apify 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 Apify for fresh data
Analytical workflows: chain Apify queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Apify in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Apify immediately.
"List all actors in my Apify account."
"Run the 'Instagram Scraper' with input { "hashtags": ["#AI"] }."
"Show me the results from dataset 'ds_10293'."
Troubleshooting Apify MCP Server with LlamaIndex
Common issues when connecting Apify to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpApify + LlamaIndex FAQ
Common questions about integrating Apify MCP Server with LlamaIndex.