How to Use the Amazon Selling Partner MCP in LlamaIndex

Q: How do I register Amazon Selling Partner tools in LlamaIndex?

You use BasicMCPClient to connect to the MCP Server and wrap it in McpToolSpec. Then, call totoollistasync() to pass the Amazon Selling Partner tools to your LlamaIndex FunctionAgent.

Q: Can LlamaIndex index live Amazon Selling Partner inventory?

Yes, LlamaIndex can run listfbainventory and ingest the resulting data directly into a vector store. This lets your LlamaIndex agent perform semantic searches over real-time Amazon Selling Partner stock levels.

Q: How does LlamaIndex prevent hallucinations with Amazon Selling Partner catalog data?

It uses getcatalogitem to pull exact specs and indexes them as ground-truth documents in LlamaIndex. The LlamaIndex agent queries this index first, ensuring answers are backed by actual Amazon Selling Partner data.

Q: Can I filter which Amazon Selling Partner tools LlamaIndex can access?

Yes, you can use the allowedtools filter when setting up your MCP client in LlamaIndex. This lets you restrict your LlamaIndex agent to safe tools like listmarketplaces while blocking write actions.

Index Amazon Selling Partner data directly into LlamaIndex vector stores for semantic RAG.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Amazon Selling Partner MCP to LlamaIndex

Create your Vinkius account to connect Amazon Selling Partner to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Amazon Selling Partner with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build a LlamaIndex RAG pipeline for Amazon

The `list_fba_inventory` tool feeds live Amazon inventory levels directly into your LlamaIndex knowledge base. Instead of just querying an API, the LlamaIndex framework indexes these Amazon stock levels so your agent can answer complex semantic questions about your inventory. This MCP Server integration turns raw Amazon numbers into searchable context inside LlamaIndex. Your LlamaIndex RAG setup can instantly connect physical Amazon stock counts with your unstructured product documentation.

Index catalog data for semantic search in LlamaIndex

The `get_catalog_item` tool retrieves deep Amazon product metadata that LlamaIndex converts into document nodes for your vector store. Your LlamaIndex agent can run `search_catalog` to gather Amazon items, index them, and then answer natural language queries about your product lineup. This means your LlamaIndex customer support bots aren't just guessing; they are grounded in real-time Amazon catalog data. You avoid hallucinations because every LlamaIndex answer points back to an indexed Amazon ASIN.

Query Amazon financial events with LlamaIndex agents

The `list_financial_events` tool exposes your Amazon payout and fee history directly to LlamaIndex's indexing engine. Your LlamaIndex agent can aggregate these Amazon events, index the transaction details, and let you run semantic queries over your cash flow. By loading this Amazon financial data into a LlamaIndex vector index, you can ask your agent about specific fee anomalies. It combines live Amazon API data with historical LlamaIndex context to give you clear, grounded financial answers.

Setup guide

Set up Amazon Selling Partner MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Amazon Selling Partner MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Amazon Selling Partner tools.",
)
response = await agent.run("List recent Amazon Selling Partner data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Amazon Selling Partner. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Amazon Selling Partner now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Amazon Selling Partner MCP in LlamaIndex

You use `BasicMCPClient` to connect to the MCP Server and wrap it in `McpToolSpec`. Then, call `to_tool_list_async()` to pass the Amazon Selling Partner tools to your LlamaIndex `FunctionAgent`.

Yes, LlamaIndex can run `list_fba_inventory` and ingest the resulting data directly into a vector store. This lets your LlamaIndex agent perform semantic searches over real-time Amazon Selling Partner stock levels.

It uses `get_catalog_item` to pull exact specs and indexes them as ground-truth documents in LlamaIndex. The LlamaIndex agent queries this index first, ensuring answers are backed by actual Amazon Selling Partner data.

Yes, you can use the `allowed_tools` filter when setting up your MCP client in LlamaIndex. This lets you restrict your LlamaIndex agent to safe tools like `list_marketplaces` while blocking write actions.

Yes, your Amazon Selling Partner financial events and transaction data are processed locally within your LlamaIndex environment. The Vinkius MCP connection uses a zero-trust, ephemeral channel that never logs or caches your sensitive financial records.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript