How to Use the Adrecord MCP in LlamaIndex

Q: Does this MCP server support filtering for LlamaIndex?

It does. You can use the allowedtools filter to restrict which API functions your agent can access. This keeps your index focused on specific performance data.

Ground your LlamaIndex RAG applications in live Adrecord affiliate data.

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Connect Adrecord MCP to LlamaIndex

Create your Vinkius account to connect Adrecord 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.

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Setup Adrecord with LlamaIndex

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Index Adrecord data for LlamaIndex

Turn your affiliate earnings data into a queryable knowledge base. Use `list_transactions` to pull records and let LlamaIndex build a vector index for semantic search. You no longer rely on static documents. Your agents search through the actual API results to answer questions about your performance metrics.

Semantic affiliate search

Combine the `get_program_details` tool with your existing document store. Your agents compare program terms against your internal marketing guidelines to find the best fit. Everything is indexed automatically. When you ask a question about program requirements, the system retrieves the relevant data points from the API as part of the context.

Unified knowledge retrieval

Merge live Adrecord feeds with your stored research. This MCP server lets you pull `get_product_feed` items directly into your RAG pipeline for updated analysis. Your agent builds a complete picture by linking past reports with current market data. You get answers grounded in real numbers rather than generic summaries.

Setup guide

Set up Adrecord 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 Adrecord 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 Adrecord tools.",
)
response = await agent.run("List recent Adrecord data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Adrecord. 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.

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Common questions about Adrecord MCP in LlamaIndex

Yes. By passing the tool output to your indexer, you convert raw transaction records into a searchable vector format. This allows for complex natural language queries over your affiliate history.

Use the BasicMCPClient to connect to the server endpoint. Then, convert the tools into a spec and pass them to your FunctionAgent for immediate use in your RAG workflow.

You can schedule your agent to pull updated data via the tools whenever needed. This keeps your index current with the latest advertiser program changes.

It does. You can use the allowed_tools filter to restrict which API functions your agent can access. This keeps your index focused on specific performance data.

Your affiliate performance data is processed only within your local environment. We treat your transaction data as sensitive, ensuring it is never cached or exposed to external models.

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