How do I find a specific Proof ID?

You can use the `search_proofs` tool to list all active proofs. The IDs will be provided in the results, allowing you to drill down into specific versions or generate viewer links.

What kind of assets can I manage with this integration?

Ziflow supports a wide range of creative assets, including images, videos, PDFs, and live websites. The integration allows you to query and manage metadata for any asset stored in your account.

INSTANT PLUG AND PLAY

Ziflow MCP Server for CrewAIGive CrewAI instant access to 12 tools to Create Proof, Create Webhook, Get Account Info, and more

Name: Ziflow
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 12 Tools Framework

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

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Ziflow app connector for CrewAI is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Ziflow Specialist",
    goal="Help users interact with Ziflow effectively",
    backstory=(
        "You are an expert at leveraging Ziflow 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 Ziflow "
        "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)

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

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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 Ziflow MCP Server

Connect your Ziflow account to any AI agent to automate your creative review and approval processes through natural conversation.

When paired with CrewAI, Ziflow becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Ziflow 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

Proof Management — Search for proofs, track versions, and monitor review statuses across your entire organization.
Reviewer Experience — Generate secure viewer URLs for reviewers and manage contacts/team users efficiently.
Decision Tracking — Submit approval decisions and manage integration properties for cross-platform synchronization.
Real-time Events — Configure and monitor webhooks to stay updated on proofing events in real-time.
Asset Organization — Manage assets associated with product SKUs or project codes directly through the AI interface.

The Ziflow MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Ziflow tools available for CrewAI

When CrewAI connects to Ziflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning online-proofing, creative-workflow, content-review, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_proof

Create a new proof

create_webhook

created. Create a new webhook

get_account_info

Get account profile

get_contact_by_email

Find contact by email

get_proof

Get proof details

get_proof_viewer_url

Generate review link

list_folders

List proof folders

list_integration_properties

List proof metadata

list_team_users

List all users

list_webhooks

List active webhooks

search_proofs

Search for proofs

submit_decision

Submit proof decision

Connect Ziflow to CrewAI via MCP

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

Why Use CrewAI with the Ziflow MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Ziflow 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

Ziflow + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Ziflow 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 Ziflow, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Ziflow 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 Ziflow against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Ziflow in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Ziflow immediately.

"Search for all active proofs in Ziflow."

"Generate a viewer link for proof ID '12345'."

Troubleshooting Ziflow MCP Server with CrewAI

Common issues when connecting Ziflow to CrewAI through the 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.

Ziflow + CrewAI FAQ

Common questions about integrating Ziflow 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.