Apollo.io MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
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.
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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 Apollo.io. "
"You have 8 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
The Apollo.io MCP Server provides direct access to one of the world's largest B2B databases. Connect your Apollo account to your AI agent to automate prospecting, data enrichment, and outreach workflows using natural language.
LlamaIndex agents combine Apollo.io tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Targeted Prospecting — Search for people and organizations using granular filters like job titles, industries, and locations.
- Data Enrichment — Instantly fill in missing details for people and companies. Get verified emails, phone numbers, and company insights.
- Engagement Automation — List your sales sequences and add new contacts to them directly from your chat.
- Workspace Management — Search and manage your saved contacts within your Apollo workspace.
The Apollo.io MCP Server exposes 8 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 Apollo.io to LlamaIndex via MCP
Follow these steps to integrate the Apollo.io 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 8 tools from Apollo.io
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
Apollo.io MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Apollo.io to LlamaIndex via MCP:
add_contact_to_sequence
Add contact to sequence
get_call
Get call details
get_contact
Get contact by ID
list_email_accounts
List connected email accounts
list_sequences
List sequences/campaigns
search_contacts
Search Apollo contacts
search_organizations
Search organizations
search_people
Search mixed people
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 people with the title 'CEO' in the 'Software' industry located in San Francisco."
"Enrich the organization data for 'vinkius.com'."
"Add contact 'c_123' to my 'New Year Campaign' sequence."
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.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Apollo.io 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 Apollo.io to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.