CrewAIFramework

QuickNode MCP Server

Bring Web3
to CrewAI

Name: QuickNode MCP Server
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

Learn how to connect QuickNode to CrewAI and start using 18 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

GDPR Free for Subscribers

Create Kv ListCreate Kv SetCreate StreamCreate WebhookDelete Kv SetDelete StreamDelete WebhookGet Kv ListGet Kv SetGet StreamList StreamsList WebhooksRpc Eth BlocknumberRpc Eth CallRpc Eth GetlogsRpc Eth GettransactionreceiptUpdate Kv ListUpdate Stream

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Ask AI about this MCP Server ChatGPT Claude Perplexity

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

What is the QuickNode MCP Server?

Connect your QuickNode account to any AI agent to orchestrate Web3 infrastructure through natural language. This server provides a comprehensive suite of tools to manage high-performance blockchain data pipelines and queries.

What you can do

Streams Management — Create, list, and update real-time data streams for historical and live blockchain ingestion using create_stream and list_streams.
Webhooks — Deploy webhooks from templates (like EVM wallet filters or contract events) to deliver real-time events to your HTTP endpoints via create_webhook.
KV Store — Manage key-value pairs and lists to power advanced server-side filtering logic for your streams using create_kv_list and create_kv_set.
Core RPC — Access fundamental blockchain data, such as retrieving the most recent block number using rpc_eth_blocknumber.

How it works

Subscribe to this server
Provide your QuickNode API Key and RPC URL
Start building and monitoring your Web3 infrastructure from Claude, Cursor, or any MCP client

Who is this for?

Web3 Developers — Rapidly prototype and manage data pipelines without leaving the terminal or IDE.
Data Engineers — Orchestrate complex blockchain data ingestion workflows using natural language commands.
DevOps Teams — Monitor and update infrastructure configurations, webhooks, and streams on the fly.

Built-in capabilities (18)

create_kv_list

Create a new KV Store list

create_kv_set

Create a KV Store key-value pair

create_stream

Create a new QuickNode stream

create_webhook

Create a webhook from a template

delete_kv_set

Delete a KV Store key-value pair

delete_stream

Delete a QuickNode stream

delete_webhook

Delete a QuickNode webhook

get_kv_list

Retrieve items from a KV Store list

get_kv_set

Retrieve a value from KV Store sets

get_stream

Retrieve details of a specific QuickNode stream

list_streams

List all active QuickNode streams

list_webhooks

Retrieve all QuickNode webhooks

rpc_eth_blocknumber

Returns the number of the most recent block

rpc_eth_call

Executes a new message call immediately without creating a transaction

rpc_eth_getlogs

Returns an array of all logs matching a given filter object

rpc_eth_gettransactionreceipt

Returns the receipt of a transaction by hash

update_kv_list

Add or remove items from a KV Store list

update_stream

Update an existing QuickNode stream

Why CrewAI?

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

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

See it in action

QuickNode in CrewAI

AI Agent→Vinkius

High Security·Kill Switch·Plug and Play

Why Vinkius

QuickNode and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect QuickNode to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.

4,000+MCP Servers ready

<40msCold start

60%Token savings

	Raw MCP	Vinkius
Server catalog	Find and host yourself	4,000+ managed
Infrastructure	Self-hosted	Sandboxed V8 isolates
Credential handling	Plaintext in config	Vault + runtime injection
Data loss prevention	None	Configurable DLP policies
Kill switch	None	Global instant shutdown
Financial circuit breakers	None	Per-server limits + alerts
Audit trail	None	Ed25519 signed logs
SIEM log streaming	None	Splunk, Datadog, Webhook
Honeytokens	None	Canary alerts on leak
Custom domains	Not applicable	DNS challenge verified
GDPR compliance	Manual effort	Automated purge + export

Unlock for AI Agents View step-by-step setup guide for CrewAI →

Enterprise Security

Why teams choose Vinkius for QuickNode in CrewAI

The QuickNode 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. All 18 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

Unlock for AI Agents View full QuickNode details →

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

The Vinkius Advantage

How Vinkius secures
QuickNode for CrewAI

Every tool call from CrewAI to the QuickNode MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start

Ed25519Signed audit chain

60%Token savings

FAQ

Frequently asked questions

How do I check the current block height on Ethereum?

You can use the rpc_eth_blocknumber tool. It will return the most recent block number from the blockchain network connected to your RPC URL.

Can I create a stream to monitor specific blockchain datasets?

Yes, use the create_stream tool. You can specify the dataset (e.g., 'block', 'traces') and the destination (e.g., 'webhook', 's3') to start ingesting data immediately.

How do I manage lists for my stream filters?

Use the create_kv_list tool to initialize a list and update_kv_list to add or remove items. These lists can be referenced in your Streams JavaScript filter functions.

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.