Apollo.io MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Add To Sequence, Enrich Company Data, Enrich Person Data, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Apollo.io 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 Apollo.io app connector for LlamaIndex is a standout in the Growth Engine 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 Apollo.io. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Apollo.io?"
)
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 Apollo.io MCP Server
Connect your Apollo.io account to any AI agent and take full control of your B2B prospecting and sales engagement workflows through natural conversation.
LlamaIndex agents combine Apollo.io 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
- Prospect Orchestration — Search through a massive database of professionals by title, location, and company domains programmatically in real-time
- Data Enrichment Intelligence — Programmatically retrieve verified email addresses, phone numbers, and high-fidelity social metadata for any contact or company
- Sequence Lifecycle Management — Enroll qualified leads into automated email sequences and monitor your sales outreach pipeline directly through your agent
- Company Architecture — Access deep firmographic data, including revenue, headcount, and technology stacks to maintain a perfectly coordinated account strategy
- Operational Monitoring — Track your remaining search and enrichment credits and monitor API connectivity directly through your agent for instant reporting
The Apollo.io 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 Apollo.io tools available for LlamaIndex
When LlamaIndex connects to Apollo.io through Vinkius, your AI agent gets direct access to every tool listed below — spanning b2b-data, prospecting, 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.
Enroll contact in sequence
Get company metadata
Get full profile details
Get API and account status
Get usage and credits
Get contact by ID
Get sender accounts
List email sequences
List your contacts
List account users
Find organizations
Find prospects
Connect Apollo.io to LlamaIndex via MCP
Follow these steps to wire Apollo.io 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 Apollo.io MCP Server
LlamaIndex provides unique advantages when paired with Apollo.io through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Apollo.io tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Apollo.io tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Apollo.io, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Apollo.io tools were called, what data was returned, and how it influenced the final answer
Apollo.io + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Apollo.io MCP Server delivers measurable value.
Hybrid search: combine Apollo.io real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Apollo.io 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 Apollo.io for fresh data
Analytical workflows: chain Apollo.io queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Apollo.io in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Apollo.io immediately.
"Find the 'VP of Engineering' at 'vinkius.com'."
"Show the tech stack and revenue for 'apple.com'."
"Enroll contact '123' into sales sequence '456'."
Troubleshooting Apollo.io MCP Server with LlamaIndex
Common issues when connecting Apollo.io to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpApollo.io + LlamaIndex FAQ
Common questions about integrating Apollo.io MCP Server with LlamaIndex.