PhantomBuster MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add PhantomBuster as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 PhantomBuster. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in PhantomBuster?"
)
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 PhantomBuster MCP Server
Connect your PhantomBuster account to any AI agent and take full control of your lead generation and web automation workflows through natural conversation.
LlamaIndex agents combine PhantomBuster 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
- Agent Oversight — List all your Phantoms and workflows to maintain visibility over your automation suite.
- Automation Control — Launch and abort Phantoms directly through the agent, including support for custom arguments.
- Result Retrieval — Fetch the latest outputs and data extracted by your Phantoms for immediate analysis.
- Configuration Auditing — Review the setup and arguments of any Phantom to verify your automation logic.
- Usage Monitoring — Get account settings and usage info to track your available execution time.
The PhantomBuster 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.
How to Connect PhantomBuster to LlamaIndex via MCP
Follow these steps to integrate the PhantomBuster MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from PhantomBuster
Why Use LlamaIndex with the PhantomBuster MCP Server
LlamaIndex provides unique advantages when paired with PhantomBuster through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine PhantomBuster tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain PhantomBuster tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query PhantomBuster, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what PhantomBuster tools were called, what data was returned, and how it influenced the final answer
PhantomBuster + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the PhantomBuster MCP Server delivers measurable value.
Hybrid search: combine PhantomBuster real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query PhantomBuster 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 PhantomBuster for fresh data
Analytical workflows: chain PhantomBuster queries with LlamaIndex's data connectors to build multi-source analytical reports
PhantomBuster MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect PhantomBuster to LlamaIndex via MCP:
abort_phantom
Stop a running Phantom
get_phantom
Get details for a specific Phantom
get_phantom_output
Get output/results from a Phantom
get_phantom_setup
Get configuration arguments for a Phantom
get_phantombuster_account
Get account settings and usage info
get_workflow
Get details for a specific workflow
launch_phantom
Start a Phantom execution
list_containers
List all Phantom containers
list_phantoms
List all Phantom agents
list_workflows
List all automation workflows
Example Prompts for PhantomBuster in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with PhantomBuster immediately.
"List all Phantoms in my account and show their current status."
"Launch the 'LinkedIn Search Export' Phantom with ID '12345'."
"Show me the extracted data from the last run of Phantom 12345."
Troubleshooting PhantomBuster MCP Server with LlamaIndex
Common issues when connecting PhantomBuster to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPhantomBuster + LlamaIndex FAQ
Common questions about integrating PhantomBuster MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect PhantomBuster with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect PhantomBuster to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.