How to Use the Commission Factory MCP in LlamaIndex
Index your Commission Factory performance metrics into LlamaIndex for grounded, queryable insights.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Commission Factory MCP to LlamaIndex
Create your Vinkius account to connect Commission Factory 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.
Build a searchable knowledge base with LlamaIndex
Convert `list_merchant_transactions` output into vector embeddings. You query your own historical performance using natural language. This MCP Server provides the raw data points that LlamaIndex turns into searchable context. You stop guessing and start querying your actual sales history.
Automated reporting via LlamaIndex agents
The `get_performance_summary` tool gives you the numbers you need to feed into RAG applications. LlamaIndex then summarizes these figures into plain English reports. Your agent builds a knowledge graph of your affiliate relationships. It uses `list_merchant_affiliates` to map out your network structure automatically.
Extract insights from merchant promotions
Index the results of `list_promotions` to keep your agent informed about current marketing campaigns. It references these codes when answering your questions. Updating your index is a single call away. You always have a fresh view of what is available across the network.
Set up Commission Factory MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 Commission Factory MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 Commission Factory tools.",
)
response = await agent.run("List recent Commission Factory data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Commission Factory. 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
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Real-time monitoring
Live
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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
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place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Commission Factory MCP in LlamaIndex
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the Commission Factory MCP today
We host it, we monitor it, we maintain it. You just paste one token.