How to Use the Biconomy (Account Abstraction) MCP in LlamaIndex

Q: How does LlamaIndex query Biconomy (Account Abstraction) quotes?

The agent calls getquote through the MCP tool spec to fetch live pricing. LlamaIndex then injects this raw JSON payload into its current context window for immediate decision-making.

Q: Can I index Biconomy (Account Abstraction) execution statuses in LlamaIndex?

Yes, you query getexplorerstatus and feed the output into your vector store. This lets you build a searchable history of all your account abstraction transactions.

Q: How do I execute a Biconomy (Account Abstraction) supertransaction using LlamaIndex?

You pass the signed quote payload to the executesupertx tool. The agent retrieves the signed object from its memory and triggers the execution.

Index Biconomy transaction data and execute gasless Supertransactions directly from your LlamaIndex RAG pipelines.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Biconomy (Account Abstraction) MCP to LlamaIndex

Create your Vinkius account to connect Biconomy (Account Abstraction) 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.

GDPR Free for Subscribers

Setup Biconomy (Account Abstraction) with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build a searchable index of Biconomy quotes

The `get_quote` tool fetches live Supertransaction quotes that you can index into your vector store. LlamaIndex stores these gas estimates and route details for semantic retrieval later. When your agent needs to compare historical execution costs, it queries the index instead of making redundant API calls. This saves time and keeps your transaction history structured.

Execute transactions through LlamaIndex MCP Server

The `execute_supertx` tool processes your signed quotes to commit transactions to the blockchain. You must supply the complete quote object containing the signatures inside the `payloadToSign` property. The agent retrieves the correct signed payload from its context, then invokes this tool to finalize the action. It keeps a clean, traceable log of every execution step.

Check transaction status for index updates

The `get_explorer_status` tool reads the current state of any Supertransaction from the Biconomy network. Your pipeline uses this data to update your local vector database with the final execution status. This ensures your RAG application always works with accurate, grounded records of completed transactions. You avoid hallucinations about whether a transaction actually went through.

Setup guide

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

Get your connection token →

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

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Biconomy (Account Abstraction) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Biconomy (Account Abstraction) MCP in LlamaIndex

The agent calls `get_quote` through the MCP tool spec to fetch live pricing. LlamaIndex then injects this raw JSON payload into its current context window for immediate decision-making.

Yes, you query `get_explorer_status` and feed the output into your vector store. This lets you build a searchable history of all your account abstraction transactions.

You pass the signed quote payload to the `execute_supertx` tool. The agent retrieves the signed object from its memory and triggers the execution.

The underlying MCP client allows asynchronous tool calls for all three endpoints. This prevents blocking your main query pipeline while waiting for on-chain status updates.

The MCP server processes transaction signatures and quote objects purely in memory without persistent storage. Since the signing occurs on your local machine, your private keys are never exposed to the network.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript