Privy MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Batch Create Wallets, Create User, Create Wallet, and more

Name: Privy
Price: 29 USD
Availability: InStock
Rating: 2.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Privy as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Privy MCP Server for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 12 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Privy. "
            "You have 12 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Privy?"
    )
    print(response)

asyncio.run(main())

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

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V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Privy MCP Server

Connect your Privy application to any AI agent to streamline user onboarding and wallet management in your Web3 application through natural language.

LlamaIndex agents combine Privy tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

User Management — Create new users, search for existing ones by term or email, and retrieve full profile metadata.
Embedded Wallets — Provision new wallets (Ethereum, Solana, Bitcoin, Sui) for your users individually or in batches of up to 100.
Wallet Operations — Update wallet metadata, policies, and ownership, or retrieve specific wallet details via ID.
Blockchain Actions — Execute RPC methods like signing messages or sending transactions directly through managed wallets.
Data Maintenance — Securely delete user records when they are no longer needed.

The Privy MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Privy tools available for LlamaIndex

When LlamaIndex connects to Privy through Vinkius, your AI agent gets direct access to every tool listed below — spanning web3, embedded-wallets, user-onboarding, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

batch

Batch create wallets on Privy

Batch create wallets

create

Create user on Privy

Create a new user object with linked accounts

create

Create wallet on Privy

Create a new wallet

delete

Delete user on Privy

Delete a user

get

Get transaction on Privy

Get a transaction

get

Get transaction by external id on Privy

Get a transaction by external ID

get

Get user on Privy

Get a user by ID

get

Get user by email on Privy

Get a user by email address

get

Get wallet on Privy

Get wallet details

Search users on Privy

Search for users

update

Update wallet on Privy

Update a wallet

wallet

Wallet rpc on Privy

Perform a wallet RPC action

Connect Privy to LlamaIndex via MCP

Follow these steps to wire Privy into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 12 tools from Privy

Why Use LlamaIndex with the Privy MCP Server

LlamaIndex provides unique advantages when paired with Privy through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Privy tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Privy tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Privy, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Privy tools were called, what data was returned, and how it influenced the final answer

Privy + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Privy MCP Server delivers measurable value.

Hybrid search: combine Privy real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Privy to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Privy for fresh data

Analytical workflows: chain Privy queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Privy in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Privy immediately.

"Search for users with the term 'beta-tester' in Privy."

"Create a new Ethereum wallet with the display name 'Main Treasury'."

"Get the user details for email 'alice@company.com'."

Troubleshooting Privy MCP Server with LlamaIndex

Common issues when connecting Privy to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Privy + LlamaIndex FAQ

Common questions about integrating Privy MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.