How to Use the SleekFlow MCP in CrewAI

Q: How do I get all contacts using SleekFlow and CrewAI?

The 'Researcher' agent calls listcontacts first. Then, another specialized agent takes those results and runs getcontactdetails for each one to build a complete profile.

Q: Can I manage message sending with SleekFlow and CrewAI?

Yes. The 'Action' agent uses the sendmessage tool, ensuring that replies are sent correctly across all channels listed by the MCP Server.

Q: How do I monitor conversations using SleekFlow and CrewAI?

The system runs listconversations continuously. This lets your agent team know immediately when a conversation starts or changes, allowing them to respond autonomously.

Q: Does this MCP Server support advanced tool filtering for CrewAI?

Yes. You can use the advanced toolfilter feature of the MCPServerHTTP class to expose only the specific tools your agents need, keeping complexity down.

Run autonomous operations by building specialized agent teams with CrewAI's multi-agent framework.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect SleekFlow MCP to CrewAI

Create your Vinkius account to connect SleekFlow to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup SleekFlow with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Coordinated Data Gathering

You can set up a team where one agent runs `list_contacts` and passes the resulting IDs to a second agent. That second agent then calls `get_contact_details` for every single contact, building a complete picture automatically.

Autonomous Messaging Pipelines

A specialized 'Responder' agent can monitor activity using `list_conversations`. When a new conversation starts, it triggers the 'Action' agent to call `send_message` without human intervention. This is full automation.

Dynamic Process Mapping

If you need to know how your customer journey is mapped out, one agent runs `list_automation_flows`. Another can then use that list of flows to decide the next best action for a specific contact record.

Setup guide

Set up SleekFlow MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke SleekFlow tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="SleekFlow Analyst",
    goal="Access and analyze SleekFlow data via MCP.",
    backstory="Expert analyst with direct SleekFlow access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent SleekFlow transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="SleekFlow Analyst",
        goal="Access and analyze SleekFlow data via MCP.",
        backstory="Expert analyst with direct SleekFlow access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent SleekFlow transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by SleekFlow. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect SleekFlow now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about SleekFlow MCP in CrewAI

The 'Researcher' agent calls `list_contacts` first. Then, another specialized agent takes those results and runs `get_contact_details` for each one to build a complete profile.

Yes. The 'Action' agent uses the `send_message` tool, ensuring that replies are sent correctly across all channels listed by the MCP Server.

The system runs `list_conversations` continuously. This lets your agent team know immediately when a conversation starts or changes, allowing them to respond autonomously.

Yes. You can use the advanced `tool_filter` feature of the MCPServerHTTP class to expose only the specific tools your agents need, keeping complexity down.

The server touches contact details and message history. Specifically, it handles labels (`list_contact_labels`) and raw conversational text from `list_conversations`.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript