How to Use the Impact.com MCP in LlamaIndex

Q: How do I index Impact.com data using LlamaIndex?

Use llama-index-tools-mcp to load the tools into your LlamaIndex environment. The agent calls listcontracts or listcampaigns and indexes the returned JSON directly into a VectorStoreIndex.

Q: Can I run semantic search over Impact.com payouts in LlamaIndex?

Yes, by indexing the output of listpayouts into LlamaIndex. You can then query the index to locate specific payment anomalies or trends using natural language.

Q: How does LlamaIndex prevent hallucinations when reading Impact.com ads?

The agent reads live ad data using listads and injects it directly into the prompt context. This forces LlamaIndex to base its answers on actual active creatives rather than pre-trained knowledge.

Q: Can I filter which Impact.com tools are exposed to LlamaIndex via this MCP Server?

You can use the allowedtools filter in the MCP client to expose only specific tools. This lets you restrict the agent to read-only tools like listcampaigns while hiding administrative actions.

Index live Impact.com partnership data into your LlamaIndex vector store using this MCP Server.

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Connect Impact.com MCP to LlamaIndex

Create your Vinkius account to connect Impact.com 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 Impact.com with LlamaIndex

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Index active contracts with this MCP Server

The `list_contracts` tool pulls active partnership terms directly into your LlamaIndex document pipeline. This tool feeds raw text agreements into your indexing system, turning flat API responses into searchable vector nodes. You can query this index to find specific commission rates or payout terms without manually searching the dashboard. LlamaIndex uses these nodes to ground your agent's answers in actual contract data.

Build a queryable ledger of transaction history

The `list_transactions` tool extracts live financial data from your account to update your RAG knowledge base. This keeps your vector store synchronized with the latest conversions and partner payouts. When you ask your LlamaIndex agent about recent partner earnings, it queries this vector index instead of guessing. This eliminates hallucinations by forcing the model to cite specific transaction records.

Semantically search your media partner network

The `list_media_partners` tool fetches details on your active affiliates and feeds them to your indexing pipeline. Your index stores partner profiles, promotional methods, and contact details as searchable vectors. You can search your affiliate network using natural language queries to find partners matching specific criteria. This replaces complex SQL queries with direct semantic searches across your partner database.

Setup guide

Set up Impact.com 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 Impact.com 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 Impact.com tools.",
)
response = await agent.run("List recent Impact.com 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 Impact.com. 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 Impact.com MCP in LlamaIndex

Use `llama-index-tools-mcp` to load the tools into your LlamaIndex environment. The agent calls `list_contracts` or `list_campaigns` and indexes the returned JSON directly into a VectorStoreIndex.

Yes, by indexing the output of `list_payouts` into LlamaIndex. You can then query the index to locate specific payment anomalies or trends using natural language.

The agent reads live ad data using `list_ads` and injects it directly into the prompt context. This forces LlamaIndex to base its answers on actual active creatives rather than pre-trained knowledge.

You can use the `allowed_tools` filter in the MCP client to expose only specific tools. This lets you restrict the agent to read-only tools like `list_campaigns` while hiding administrative actions.

Your transactions and payouts are processed inside an MCP Server sandbox on Vinkius. No financial data is cached or stored on the hosting platform; it flows directly into your private LlamaIndex vector store.

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