How to Use the Increase MCP in LlamaIndex

Q: How can I increase the data accuracy of my LlamaIndex app?

You increase accuracy by indexing live increaselisttransactions output. By querying the raw ledger, your agent stays grounded in the actual state of your bank accounts.

Q: Can I index simulated inbound ACH transfers?

You can use increasesimulateinboundach in the sandbox to test your RAG indexing logic. This ensures your system handles incoming transactions correctly before moving to production.

Index your live banking data into LlamaIndex for intelligent, grounded financial queries.

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Connect Increase MCP to LlamaIndex

Create your Vinkius account to connect Increase 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 Increase with LlamaIndex

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Query your financial history with LlamaIndex

Convert transaction logs into a searchable knowledge base. Use `increase_list_transactions` to pull your history and feed it straight into your vector store for semantic analysis. Ask questions about your spending patterns or specific wire transfers. Your agent provides answers based on the live data retrieved from the server.

Ground your financial decisions in real data

Avoid hallucinations by connecting LlamaIndex to live bank states. Fetch current balances with `increase_get_balance` before your agent suggests any financial action. Your index stays fresh because it pulls from the source of truth. The agent makes decisions based on reality, not stale estimates.

Automate account provisioning for your index

Provision new accounts and routing numbers programmatically. Use `increase_create_account` to trigger the creation process, then index the resulting details for future reference. Manage your entire financial architecture through your agent. It tracks all created assets within your internal index.

Setup guide

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

You increase accuracy by indexing live `increase_list_transactions` output. By querying the raw ledger, your agent stays grounded in the actual state of your bank accounts.

It provides context-rich data for your RAG pipeline. You increase the relevance of your agent's answers by grounding them in real-time financial records rather than static text files.

Yes, you can index your audit logs to answer complex compliance questions instantly. This allows you to increase the speed of your internal reviews without manual data scraping.

The server operates in a zero-trust sandbox. Your banking data, including account numbers, is never logged or cached by the Vinkius infrastructure.

You can use `increase_simulate_inbound_ach` in the sandbox to test your RAG indexing logic. This ensures your system handles incoming transactions correctly before moving to production.

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