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RocketReach MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Lookup Status, Create Webhook, Delete Webhook, and more

Built by Vinkius GDPR 12 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add RocketReach 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 RocketReach app connector for LlamaIndex is a standout in the Industry Titans 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

python
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 RocketReach. "
            "You have 12 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in RocketReach?"
    )
    print(response)

asyncio.run(main())
RocketReach
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 RocketReach MCP Server

Connect your RocketReach account to any AI agent and take full control of your B2B lead generation and contact enrichment orchestration through natural conversation. RocketReach provides a premier platform for finding verified emails and phone numbers, and this integration allows you to search for professionals, retrieve company metadata, and manage webhooks directly from your chat interface.

LlamaIndex agents combine RocketReach 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

  • Lead & Person Orchestration — Search for professionals by name, title, or company and retrieve detailed profile metadata programmatically.
  • Contact Enrichment Intelligence — Perform instant lookups for specific individuals using RocketReach IDs or LinkedIn URLs to reveal verified contact info directly from the AI interface.
  • Company & Firmographic Control — Search and retrieve detailed company profiles, including domains and employee counts via natural language.
  • Usage & Credit Oversight — Access real-time account profile metadata and monitor credit usage to ensure your outreach campaigns are always optimized.
  • Operational Monitoring — Track system activity, manage webhooks, and retrieve billing info using simple AI commands.

The RocketReach 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 RocketReach tools available for LlamaIndex

When LlamaIndex connects to RocketReach through Vinkius, your AI agent gets direct access to every tool listed below — spanning b2b-database, contact-enrichment, verified-emails, 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.

check_lookup_status

Check async lookup status

create_webhook

complete. Create a new webhook

delete_webhook

Delete a webhook

get_account_info

Get account profile

get_billing_info

Get billing details

get_credit_usage

Get credit usage stats

list_recent_searches

List search history

list_webhooks

List configured webhooks

lookup_company

Get company details

lookup_person

Consumes 1 credit. Get verified contact info

search_companies

Search for companies

search_people

Search for professionals

Connect RocketReach to LlamaIndex via MCP

Follow these steps to wire RocketReach into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 12 tools from RocketReach

Why Use LlamaIndex with the RocketReach MCP Server

LlamaIndex provides unique advantages when paired with RocketReach through the Model Context Protocol.

01

Data-first architecture: LlamaIndex agents combine RocketReach tool responses with indexed documents for comprehensive, grounded answers

02

Query pipeline framework lets you chain RocketReach tool calls with transformations, filters, and re-rankers in a typed pipeline

03

Multi-source reasoning: agents can query RocketReach, a vector store, and a SQL database in a single turn and synthesize results

04

Observability integrations show exactly what RocketReach tools were called, what data was returned, and how it influenced the final answer

RocketReach + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the RocketReach MCP Server delivers measurable value.

01

Hybrid search: combine RocketReach real-time data with embedded document indexes for answers that are both current and comprehensive

02

Data enrichment: query RocketReach to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying RocketReach for fresh data

04

Analytical workflows: chain RocketReach queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for RocketReach in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with RocketReach immediately.

01

"Search for 'John Doe' who works at 'Google'."

02

"Search for VP of Engineering contacts at Series B SaaS companies in San Francisco."

03

"Look up the complete profile and contact information for the CEO of Meridian Corp."

Troubleshooting RocketReach MCP Server with LlamaIndex

Common issues when connecting RocketReach to LlamaIndex through the Vinkius, and how to resolve them.

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

RocketReach + LlamaIndex FAQ

Common questions about integrating RocketReach MCP Server with LlamaIndex.

01

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query RocketReach tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.