How to Use the Copperx MCP in LlamaIndex

Q: Can LlamaIndex filter Copperx tools?

Use the allowedtools filter to limit which operations your agent can perform. This prevents unauthorized access to sensitive payment functions.

Index your Copperx payment data into LlamaIndex to build searchable knowledge bases for your agents.

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Connect Copperx MCP to LlamaIndex

Create your Vinkius account to connect Copperx 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 Copperx with LlamaIndex

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Index Copperx records with LlamaIndex

Turn your payment history into a searchable index. `list_payments` output gets ingested directly into your vector store for future retrieval. Your agent uses this data to answer questions about transaction history. It grounds responses in actual financial records rather than guessing.

Query live customer data

Retrieve customer profiles using `list_customers` and add them to your knowledge graph. LlamaIndex keeps this information ready for semantic search. Your agent identifies customers by querying the index you built. It connects identity properties to specific payment events without manual lookups.

Analyze wallet balances

Fetch real-time crypto balances with `get_wallet_balance` and store them for historical analysis. This provides your agent with a current view of your treasury. Comparing past and current balance snapshots helps your agent track performance. You get a clear picture of your financial state inside your LlamaIndex apps.

Setup guide

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

Install the MCP tool spec, initialize the client with the endpoint, and pass the tools to your FunctionAgent. The agent then indexes the results automatically.

Yes, the tool outputs act as data sources for your vector store. You can query your payment history as part of your RAG pipeline.

We keep your customer names and email addresses behind our secure V8 sandbox. Only the indexed results you choose to store are accessible to the agent.

Use the allowed_tools filter to limit which operations your agent can perform. This prevents unauthorized access to sensitive payment functions.

Yes, use the provided async tool spec. It ensures your agent maintains performance while fetching large datasets from the server.

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