AeroLeads MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Add New Lead, Delete Lead, Find Email By Name, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add AeroLeads 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 AeroLeads app connector for LlamaIndex is a standout in the Sales Automation category — giving your AI agent 12 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 AeroLeads. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in AeroLeads?"
)
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 AeroLeads MCP Server
Connect your AeroLeads account to any AI agent and take full control of your B2B lead generation and high-fidelity contact enrichment workflows through natural conversation.
LlamaIndex agents combine AeroLeads tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Verified Email Orchestration — Instantly find professional email addresses using prospect names and company domains with high-fidelity verification status
- LinkedIn Enrichment Intelligence — Programmatically retrieve over 60 data points from LinkedIn URLs, including verified phone numbers, job roles, and skills
- Prospect Lifecycle Management — List and manage your captured leads programmatically, or create new high-fidelity records directly through your agent
- Domain Discovery Architecture — Find all professional contacts associated with a specific company domain to identify key decision-makers programmatically
- Operational Monitoring — Track your remaining account credits and monitor team activity directly through your agent for instant performance reporting
The AeroLeads MCP Server exposes 12 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 12 AeroLeads tools available for LlamaIndex
When LlamaIndex connects to AeroLeads through Vinkius, your AI agent gets direct access to every tool listed below — spanning b2b-prospecting, email-verification, lead-enrichment, 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.
Manually add lead
Remove captured lead
Find email by name
Get profile info
Get credit status
Get full lead info
Enrich LinkedIn profile
List your leads
List lead lists
List account users
List active webhooks
Find leads in domain
Connect AeroLeads to LlamaIndex via MCP
Follow these steps to wire AeroLeads 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 AeroLeads MCP Server
LlamaIndex provides unique advantages when paired with AeroLeads through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine AeroLeads tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain AeroLeads tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query AeroLeads, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what AeroLeads tools were called, what data was returned, and how it influenced the final answer
AeroLeads + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the AeroLeads MCP Server delivers measurable value.
Hybrid search: combine AeroLeads real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query AeroLeads 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 AeroLeads for fresh data
Analytical workflows: chain AeroLeads queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for AeroLeads in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with AeroLeads immediately.
"Find the email for 'Elon Musk' at 'tesla.com'."
"Enrich the profile for this LinkedIn URL: 'https://linkedin.com/in/example'."
"Search for all leads in the 'vinkius.com' domain."
Troubleshooting AeroLeads MCP Server with LlamaIndex
Common issues when connecting AeroLeads to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAeroLeads + LlamaIndex FAQ
Common questions about integrating AeroLeads MCP Server with LlamaIndex.