Privy MCP Server for LangChainGive LangChain 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

LangChain is the leading Python framework for composable LLM applications. Connect Privy through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this MCP Server for LangChain

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The Privy MCP Server for LangChain 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

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

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Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "privy": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Privy, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

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.

LangChain's ecosystem of 500+ components combines seamlessly with Privy through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain

When LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from Privy via MCP

Why Use LangChain with the Privy MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Privy MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Privy queries for multi-turn workflows

Privy + LangChain Use Cases

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

RAG with live data: combine Privy tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Privy, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Privy tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Privy tool call, measure latency, and optimize your agent's performance

Example Prompts for Privy in LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Privy + LangChain FAQ

Common questions about integrating Privy MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.