How do I find the Workspace ID for my Flow account?

You can use the 'list_workspaces' tool. The agent will retrieve all workspaces you have access to and return their names and unique IDs, which you can then use for other operations.

Can I mark a task as completed using the agent?

Yes! Use the 'update_task' tool, provide the Task ID, and set the 'status' parameter to 'completed'. The task will be immediately updated in Flow.

How do I see the discussion history for a task?

Use the 'list_task_comments' tool and provide the Task ID. The agent will retrieve all messages and replies associated with that task, allowing you to catch up on the discussion.

Flow MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Flow
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

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

Connect your Flow account to any AI agent and automate your project management and team collaboration through the Model Context Protocol (MCP). Flow (getflow.com) provides a clean and powerful platform for organizing work, tracking task progress, and facilitating team discussions. Now, you can manage your workspaces, projects, and individual tasks directly through natural conversation.

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

What you can do

Project Coordination — List all projects within your workspaces and retrieve detailed metadata, including ownership and due dates.
Task Management — Create, update, and list tasks across workspaces, projects, or specific task lists. Change statuses (incomplete/completed) instantly.
Organized Lists — Access and list task groups (Lists) within projects to maintain a clear hierarchy of work.
Team Interaction — List all workspace members and teams, and participate in task discussions by reading or adding comments.
Workspace Oversight — Get a high-level view of all the top-level workspaces you belong to.
Real-time Updates — Fetch specific task details or metadata to keep your team informed and your projects on track.

The Flow 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.

How to Connect Flow to CrewAI via MCP

Follow these steps to integrate the Flow MCP Server with CrewAI.

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 Flow

Why Use CrewAI with the Flow MCP Server

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

Flow + CrewAI Use Cases

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

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

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

Flow MCP Tools for CrewAI (12)

These 12 tools become available when you connect Flow to CrewAI via MCP:

add_task_comment

create_task

Create a new task

get_project

Get project details

get_task

Get task details

list_projects

List projects in workspace

list_task_comments

List task discussions

list_task_lists

List lists in project

list_tasks

List tasks

list_workspace_members

List team members

list_workspace_teams

List workspace teams

list_workspaces

List top-level workspaces

update_task

). Update an existing task

Example Prompts for Flow in CrewAI

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

"List all my Flow projects in the 'Marketing' workspace."

"Create a new task: 'Review final design mockup' in the 'Design' list."

"Add a comment to task 'task_123': 'Design looks great, proceed to coding'."

Troubleshooting Flow MCP Server with CrewAI

Common issues when connecting Flow 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

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

Flow + CrewAI FAQ

Common questions about integrating Flow 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.