How to Use the Dynamic (Web3 Auth) MCP in LlamaIndex

Q: Can I query Dynamic (Web3 Auth) user profiles inside LlamaIndex?

Yes, you use getuser to pull profiles and index them as document nodes. This allows your LlamaIndex agent to search and retrieve Web3 user metadata semantically using this MCP integration.

Q: Does LlamaIndex support Dynamic (Web3 Auth) webhook lookups?

Yes, the agent calls getwebhooks to inspect configured event endpoints. This metadata is indexed to help you verify active integrations without leaving your search interface.

Q: How does the agent handle sanctions verification?

The agent invokes checksanctions to inspect a wallet before indexing its data. If the wallet is flagged, the pipeline halts indexing to keep your knowledge base clean.

Index Dynamic user profiles and wallet balances directly into your LlamaIndex vector store for semantic context.

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Connect Dynamic (Web3 Auth) MCP to LlamaIndex

Create your Vinkius account to connect Dynamic (Web3 Auth) 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 Dynamic (Web3 Auth) with LlamaIndex

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Index Web3 profile metadata

The `get_user` tool pulls user profile data from Dynamic to populate your LlamaIndex knowledge graphs. This MCP server helps your RAG pipeline index these user records so your agent can query profile history without hitting the API twice. LlamaIndex converts the JSON payload into document nodes. This lets you run semantic searches over your user base, matching profile attributes to user queries instantly.

Query token balances via LlamaIndex MCP Server

The `get_token_balances` tool retrieves active on-chain assets to ground your RAG queries in reality. Your LlamaIndex agent queries this tool to verify what a user owns before answering financial questions. This prevents hallucinations about wallet holdings. By indexing the live balance data, your agent answers questions using actual wallet state instead of guessing.

Clean up user data on demand

The `delete_user` tool purges user records from your Dynamic environment when a user requests account deletion. Your LlamaIndex pipeline triggers this tool and simultaneously removes their vector index nodes. This keeps your database and your semantic index in sync. You avoid querying dead user profiles because the agent cleans up both systems in a single run.

Setup guide

Set up Dynamic (Web3 Auth) 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 Dynamic (Web3 Auth) 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 Dynamic (Web3 Auth) tools.",
)
response = await agent.run("List recent Dynamic (Web3 Auth) data")

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Common questions about Dynamic (Web3 Auth) MCP in LlamaIndex

Yes, you use `get_user` to pull profiles and index them as document nodes. This allows your LlamaIndex agent to search and retrieve Web3 user metadata semantically using this MCP integration.

Run the llama-index-tools-mcp package and initialize the client. This MCP tool list passes to your LlamaIndex agent to enable live wallet queries.

Yes, the agent calls `get_webhooks` to inspect configured event endpoints. This metadata is indexed to help you verify active integrations without leaving your search interface.

The agent invokes `check_sanctions` to inspect a wallet before indexing its data. If the wallet is flagged, the pipeline halts indexing to keep your knowledge base clean.

User profiles, wallet addresses, and token balances are processed inside an ephemeral V8 sandbox. LlamaIndex stores the resulting vector embeddings in your private database, ensuring your credentials are never exposed to external servers.

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