Afosto MCP Server for LlamaIndex 4 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Afosto 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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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 Afosto. "
"You have 4 tools available."
),
)
response = await agent.run(
"What tools are available in Afosto?"
)
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 Afosto MCP Server
Connect your Afosto Retail Engine account to your AI agent to unlock enterprise-grade e-commerce orchestration. From managing multi-channel orders to monitoring real-time inventory across warehouses and auditing product catalogs, your agent handles your retail stack through natural conversation.
LlamaIndex agents combine Afosto tool responses with indexed documents for comprehensive, grounded answers. Connect 4 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
- Order Orchestration — List and audit multi-channel orders, check fulfillment statuses, and retrieve technical metadata
- Inventory Management (WMS) — Monitor real-time stock levels across multiple locations and identify replenishment needs
- Product Catalog Oversight — List products, variants, and pricing to ensure your storefront is always synchronized
- Customer Intelligence — Retrieve centralized customer profiles and interaction history to support sales and support
- Retail Insights — Quickly identify sales trends or inventory bottlenecks directly from your chat interface
The Afosto MCP Server exposes 4 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 Afosto to LlamaIndex via MCP
Follow these steps to integrate the Afosto 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 4 tools from Afosto
Why Use LlamaIndex with the Afosto MCP Server
LlamaIndex provides unique advantages when paired with Afosto through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Afosto tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Afosto tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Afosto, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Afosto tools were called, what data was returned, and how it influenced the final answer
Afosto + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Afosto MCP Server delivers measurable value.
Hybrid search: combine Afosto real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Afosto 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 Afosto for fresh data
Analytical workflows: chain Afosto queries with LlamaIndex's data connectors to build multi-source analytical reports
Afosto MCP Tools for LlamaIndex (4)
These 4 tools become available when you connect Afosto to LlamaIndex via MCP:
list_customers
Retrieve centralized customer profile data and their historic eCommerce behavior
list_inventory
Retrieve real-time inventory and stock levels aggregated by warehouse distribution
list_orders
Retrieve recent multi-channel eCommerce orders aggregated by Afosto
list_products
Retrieve the complete product catalog, highlighting active variants and their pricing
Example Prompts for Afosto in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Afosto immediately.
"List all pending orders from the last 24 hours."
"What is the current stock level for 'Wireless Headphones' in all warehouses?"
"Search for a customer profile with email 'john.doe@example.com'."
Troubleshooting Afosto MCP Server with LlamaIndex
Common issues when connecting Afosto to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAfosto + LlamaIndex FAQ
Common questions about integrating Afosto 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 Afosto 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 Afosto to LlamaIndex
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.