Can my AI create and update records in Retable?

Yes. Use `create_record` to add new rows and `update_record` to modify existing ones. Both accept a JSON string with field values.

How do I query records from a specific table?

Use `list_records` with the table ID. The agent returns all rows with their field values.

Can I delete records through the AI?

Yes. The `delete_record` tool permanently removes a row from a table by table ID and record ID.

INSTANT PLUG AND PLAY

Retable MCP Server for CrewAIGive CrewAI instant access to 10 tools to Check Retable Status, Create Record, Delete Record, and more

Name: Retable
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Retable through Vinkius, pass the Edge URL in the `mcps` parameter and every Retable 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 Retable app connector for CrewAI is a standout in the Productivity category — giving your AI agent 10 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="Retable Specialist",
    goal="Help users interact with Retable effectively",
    backstory=(
        "You are an expert at leveraging Retable 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 Retable "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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IAMAccess control

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DLPData protection

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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 Retable MCP Server

Connect your Retable account to any AI agent and manage your spreadsheet data through natural conversation.

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

Project Management — List and inspect projects
Table Access — Browse tables and view schemas
Record Operations — List, get, create, update, and delete records
Health Check — Verify API connectivity

The Retable MCP Server exposes 10 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 10 Retable tools available for CrewAI

When CrewAI connects to Retable through Vinkius, your AI agent gets direct access to every tool listed below — spanning relational-database, spreadsheet-automation, collaborative-data, 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.

check_retable_status

Verify API connectivity

create_record

Create a new record

delete_record

Delete a record

get_project

Get project details

get_record

Get record details

get_table

Get table details

list_projects

List all projects

list_records

List records in a table

list_tables

List tables in a project

update_record

Update a record

Connect Retable to CrewAI via MCP

Follow these steps to wire Retable 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 10 tools from Retable

Why Use CrewAI with the Retable MCP Server

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

Retable + CrewAI Use Cases

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

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

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

Example Prompts for Retable in CrewAI

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

"List all my Retable projects."

"Show all records in table tbl_001."

"Add a new record to table tbl_001 with name 'NewClient' and status 'New'."

Troubleshooting Retable MCP Server with CrewAI

Common issues when connecting Retable 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.

Retable + CrewAI FAQ

Common questions about integrating Retable 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.