How to Use the Saysimple MCP in CrewAI

Q: Can CrewAI agents read Saysimple templates?

Yes, give your agents access to listtemplates. They can then select the right one for any given conversation.

Q: How do I limit tool access for CrewAI agents?

Use the toolfilter parameter in your MCP configuration. This prevents agents from using sensitive tools like sendmessage.

Q: Can Saysimple webhooks trigger CrewAI crews?

Use listwebhooks to audit your setup. You can then ensure your agents are listening to the correct events for automated responses.

Deploy autonomous messaging crews with Saysimple and the CrewAI MCP Server.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Saysimple MCP to CrewAI

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

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Setup Saysimple with CrewAI

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Autonomous chat management in CrewAI

Give your agents the ability to monitor and assign conversations. Use `list_chats` to find pending work and `assign_chat` to delegate it to human staff. Your crew handles the triage while you focus on high-level strategy. It keeps your messaging queue moving without constant oversight.

Multi-agent message dispatch

Coordinate messaging tasks between specialized agents. One agent can fetch templates with `get_template` while another executes `send_message`. This setup ensures your customer outreach follows strict internal guidelines. Your agents work together to maintain conversation quality.

System-wide contact visibility

Provide your research agents with full access to customer history. Use `list_contacts` and `get_contact` to pull data for informed replies. It allows your crew to provide personalized service at scale. Your agents always operate with the full context of the customer record.

Setup guide

Set up Saysimple 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 Saysimple tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Saysimple 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="Saysimple Analyst",
        goal="Access and analyze Saysimple data via MCP.",
        backstory="Expert analyst with direct Saysimple access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Saysimple 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 →

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