Privy MCP Server for CrewAIGive CrewAI 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

Connect your CrewAI agents to Privy through Vinkius, pass the Edge URL in the `mcps` parameter and every Privy tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The Privy MCP Server for CrewAI 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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Privy Specialist",
    goal="Help users interact with Privy effectively",
    backstory=(
        "You are an expert at leveraging Privy tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Privy "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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.

When paired with CrewAI, Privy becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Privy tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI

When CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Privy

Why Use CrewAI with the Privy MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Privy through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Privy + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Privy for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Privy, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Privy tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Privy against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Privy in CrewAI

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Privy + CrewAI FAQ

Common questions about integrating Privy MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.

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