LeafLink MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add LeafLink 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 LeafLink. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in LeafLink?"
)
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 LeafLink MCP Server
Connect your LeafLink account to any AI agent to automate your cannabis wholesale operations. This MCP server enables your agent to manage product listings, monitor real-time inventory, and track received orders directly from natural language.
LlamaIndex agents combine LeafLink tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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 Oversight — List and retrieve detailed information for all wholesale orders received from buyers
- Inventory Visibility — Get real-time stock levels and availability for your entire product catalog
- Catalog Management — List, retrieve, create, and update products including pricing and metadata
- Status Transitions — Move orders through their lifecycle (accept, fulfill, cancel) via simple commands
- Partner Tracking — List registered brands and buyers to maintain clear visibility of your wholesale network
The LeafLink MCP Server exposes 9 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 LeafLink to LlamaIndex via MCP
Follow these steps to integrate the LeafLink 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 9 tools from LeafLink
Why Use LlamaIndex with the LeafLink MCP Server
LlamaIndex provides unique advantages when paired with LeafLink through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine LeafLink tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain LeafLink tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query LeafLink, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what LeafLink tools were called, what data was returned, and how it influenced the final answer
LeafLink + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the LeafLink MCP Server delivers measurable value.
Hybrid search: combine LeafLink real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query LeafLink 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 LeafLink for fresh data
Analytical workflows: chain LeafLink queries with LlamaIndex's data connectors to build multi-source analytical reports
LeafLink MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect LeafLink to LlamaIndex via MCP:
create_new_product
Requires a JSON body with product details. Add a new product to your wholesale catalog
get_order_details
Get details for a specific order
get_product_details
Get details for a specific product
list_received_orders
List all wholesale orders received
list_wholesale_brands
List all brands in your account
list_wholesale_customers
List all buyers and customers
list_wholesale_products
List all products available in your inventory
update_order_status
g., accept, fulfill, cancel, reject). Transition an order through its lifecycle
update_product_inventory
Update inventory level for a specific product
Example Prompts for LeafLink in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with LeafLink immediately.
"Show me all active wholesale orders in LeafLink."
"Check the inventory level for 'Sour Diesel Flower 3.5g'."
"Accept the order #ORD-101."
Troubleshooting LeafLink MCP Server with LlamaIndex
Common issues when connecting LeafLink to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpLeafLink + LlamaIndex FAQ
Common questions about integrating LeafLink 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 LeafLink 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 LeafLink to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.