DataDive 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 DataDive 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 DataDive. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in DataDive?"
)
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 DataDive MCP Server
Integrate DataDive, the advanced toolset for Amazon sellers, directly into your AI workflow. Monitor product niches, track keyword rankings with Rank Radar, and analyze your sales profits and inventory levels using natural language.
LlamaIndex agents combine DataDive 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
- Niche Analysis — List and retrieve detailed metrics for product niches you are tracking.
- Keyword Tracking — Monitor organic and PPC rankings for any ASIN using Rank Radar data.
- Profit Oversight — Retrieve a high-level summary of your Amazon sales and financial performance.
- Inventory Management — Check current stock levels and get restock recommendations via chat.
The DataDive 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 DataDive to LlamaIndex via MCP
Follow these steps to integrate the DataDive 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 DataDive
Why Use LlamaIndex with the DataDive MCP Server
LlamaIndex provides unique advantages when paired with DataDive through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine DataDive tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain DataDive tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query DataDive, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what DataDive tools were called, what data was returned, and how it influenced the final answer
DataDive + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the DataDive MCP Server delivers measurable value.
Hybrid search: combine DataDive real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query DataDive 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 DataDive for fresh data
Analytical workflows: chain DataDive queries with LlamaIndex's data connectors to build multi-source analytical reports
DataDive MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect DataDive to LlamaIndex via MCP:
get_account_details
Returns metadata such as account tier, connected marketplace integrations, and subscription status. Retrieve metadata for your DataDive account
get_high_volume_keywords
Returns keywords with significant search volume and favorable competition metrics for ranking priority. List top performing keywords based on search volume and competition
get_inventory_status
Returns units in stock, inbound shipments, and daily sell-through rates to provide restock lead-time alerts. Check current inventory levels and restock recommendations
get_niche_details
Resolves high-level metrics such as average price, total niche volume, and competition score based on aggregated Amazon data. Get detailed analytics and metrics for a specific niche
get_profits_summary
Aggregates sales data, fees, and advertising spend to return net profit margins and ROI for the connected seller account. Retrieve a high-level financial summary of your Amazon sales
get_rank_radar
Returns real-time organic and sponsored positions across tracked keywords, enabling competitive visibility analysis. Get keyword ranking data (organic and PPC) for a specific ASIN
list_competitor_asins
Includes product titles, brand names, and baseline performance data. List all ASINs (competitors) tracked within a niche
list_niche_keywords
Returns search volume, relevancy scores, and priority indicators for product ranking and SEO optimization. List all keywords and search volumes for a specific niche
list_product_niches
Returns a collection of niche objects including name, marketplace (e.g., Amazon US), and tracking status. List all product niches tracked in your DataDive account
search_all_keywords
Matches against the global keyword repository in the user's account to find occurrences and metrics across multiple categories. Search for keywords across all your tracked niches
Example Prompts for DataDive in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with DataDive immediately.
"Show me the ranking data for ASIN 'B08S9DF7' using Rank Radar."
"List all product niches I'm currently tracking in DataDive."
"What is my profit summary for the last 30 days?"
Troubleshooting DataDive MCP Server with LlamaIndex
Common issues when connecting DataDive to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDataDive + LlamaIndex FAQ
Common questions about integrating DataDive 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 DataDive 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 DataDive to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.