How to Use the Mercury MCP in LlamaIndex

Q: Can I run semantic search over my Mercury transaction history?

Yes. By combining LlamaIndex with the listtransactions tool, you can index transaction descriptions and search them using natural language queries.

Q: Can I filter which Mercury tools are exposed to my LlamaIndex?

Yes. You can use the allowedtools filter in LlamaIndex to restrict your agent's access to specific Mercury tools like listrecipients while hiding others.

Index live Mercury financial data directly into LlamaIndex vector stores for semantic search and RAG with this MCP Server.

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Connect Mercury MCP to LlamaIndex

Create your Vinkius account to connect Mercury 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 Mercury with LlamaIndex

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Index Mercury transaction histories for RAG

The `list_transactions` tool exposes real-time banking records so you can ingest them directly into your LlamaIndex vector store. Your agent can query past vendor payments using semantic search instead of writing complex database queries. By feeding live financial data into your index, you eliminate outdated spreadsheets. Your queries return answers grounded in actual, real-time banking history.

Build knowledge-augmented invoice search with LlamaIndex

The `list_invoices` tool lets you pull active accounts receivable data straight into your LlamaIndex knowledge base. Your agent can search across invoice notes, customer names, and outstanding amounts using natural language. This turns static invoice data into a searchable, queryable index. You get immediate answers about outstanding balances without manual filtering.

Query card lists and customer profiles using the Mercury MCP Server

The `list_cards` tool provides structured corporate card data that LlamaIndex parses into searchable nodes. Your agent can instantly locate which employee holds a specific card or match customers with their payment histories. Instead of hardcoding API filters, you let the index handle the semantic relationships. It makes finding specific cardholder details or customer profiles as simple as asking a question.

Setup guide

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

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Common questions about Mercury MCP in LlamaIndex

Use the llama-index-tools-mcp package to initialize the client, then convert the Mercury tools into a tool spec. Your LlamaIndex agent can then query tools like `get_balance` to retrieve live Mercury data for your index.

Yes. By combining LlamaIndex with the `list_transactions` tool, you can index transaction descriptions and search them using natural language queries.

Yes. The LlamaIndex agent is forced to ground its answers using live data retrieved from Mercury tools like `get_account` and `list_accounts`, ensuring factual financial reporting.

Yes. You can use the allowed_tools filter in LlamaIndex to restrict your agent's access to specific Mercury tools like `list_recipients` while hiding others.

Vinkius executes the Mercury MCP Server in an ephemeral, zero-trust V8 sandbox. This MCP setup ensures your Mercury transaction records and account structures are processed in memory and never written to persistent logs.

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