How to Use the Adtraction MCP in LlamaIndex
Index your affiliate performance data directly into LlamaIndex to build RAG apps that query Adtraction stats.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Adtraction MCP to LlamaIndex
Create your Vinkius account to connect Adtraction 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.
Index Adtraction stats for LlamaIndex RAG
Use `get_stats_by_program` to generate searchable knowledge. LlamaIndex ingests the tool output and stores it in your vector index for deep semantic retrieval. Stop guessing performance trends. Ask your agent questions about past periods and get answers grounded in your actual network data.
Query affiliate programs with LlamaIndex
Call `list_programs` to seed your knowledge base. The agent maps your active campaigns and stores the program metadata for future reference. When you ask about campaign alignment, LlamaIndex pulls from the indexed program list. It creates a unified view of your entire affiliate footprint.
Audit transactions using LlamaIndex search
The `list_transactions` tool fetches your raw activity. Indexing this data allows you to search for specific conversion patterns across your entire history. Your agent cross-references these transactions against your documentation. It avoids hallucinations by relying on the live data you indexed.
Set up Adtraction 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 Adtraction 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 Adtraction tools.",
)
response = await agent.run("List recent Adtraction data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Adtraction. 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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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
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Common questions about Adtraction MCP in LlamaIndex
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