How to Use the Retable MCP in CrewAI

Deploy a specialized agent crew in CrewAI to manage your Retable data with automated precision.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Retable MCP to CrewAI

Create your Vinkius account to connect Retable 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 Retable with CrewAI

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Role-based Retable data operations

Assign one agent to research data and another to execute updates. Your researcher uses `list_records` to find patterns, while the executor uses `update_record` to act. This separation of concerns makes your crew more reliable. Each agent has a focused purpose, reducing the chance of accidental data deletion.

Automated monitoring and response

Set up a monitor agent that periodically calls `get_table` to check for new entries. If it finds something, it triggers a chain of events to process that data. This works great for background tasks. You don't have to trigger your agents manually; they watch the database and act whenever conditions are met.

Collaborative database maintenance

Use shared memory to keep agents updated on what others have done. If one agent creates a record, the rest of the crew knows the new ID for their next steps. This creates a fluid operation where agents pass work to each other. They stay in sync without you needing to manage every single step.

Setup guide

Set up Retable 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 Retable tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Retable 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 Retable. 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.

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Common questions about Retable MCP in CrewAI

You pass the MCP Server URL to the agent's tools list. This allows the crew to access the Retable API directly during their task execution.

Yes, agents in a crew have shared memory. They can pass record IDs and data findings between each other as they collaborate on a task.

Every tool call is recorded in the agent's execution history. You can audit exactly which record was changed and by which agent.

Retable locks individual records during updates. If two agents try to write to the same row, the API handles the request queue to ensure data integrity.

The server enforces strict permissioning on all read and write calls. You define exactly which tables your agents can see, protecting your private spreadsheets from accidental exposure.

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