Kintone MCP Server for CrewAIGive CrewAI instant access to 8 tools to Add Records, Delete Records, Get App Fields, and more
GDPR Free for SubscribersConnect your CrewAI agents to Kintone through Vinkius, pass the Edge URL in the `mcps` parameter and every Kintone tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
Ask AI about this MCP Server for CrewAI
The Kintone MCP Server for CrewAI is a standout in the Productivity category — giving your AI agent 8 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminifrom crewai import Agent, Task, Crew
agent = Agent(
role="Kintone Specialist",
goal="Help users interact with Kintone effectively",
backstory=(
"You are an expert at leveraging Kintone 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 Kintone "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 8 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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 Kintone MCP Server
Connect your Kintone instance to any AI agent and manage business applications through natural conversation.
When paired with CrewAI, Kintone becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Kintone 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
- App Management — List all apps and inspect their field configurations
- Record Operations — Create, read, update, and query records in any app
- Data Queries — Search records using Kintone query syntax with field filters
- Field Access — Browse app fields and their types for data modeling
The Kintone MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 8 Kintone tools available for CrewAI
When CrewAI connects to Kintone through Vinkius, your AI agent gets direct access to every tool listed below — spanning low-code, workflow-automation, database-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Add records on Kintone
Input should be a JSON array of record objects. Add one or more records to an app
Delete records on Kintone
Delete records from an app
Get app fields on Kintone
Get app field settings
Get record on Kintone
Get details for a specific record
Get space details on Kintone
Get details for a space
List apps on Kintone
List all accessible Kintone apps
List records on Kintone
You can provide an optional query string. List records from a Kintone app
Update records on Kintone
Update one or more records
Connect Kintone to CrewAI via MCP
Follow these steps to wire Kintone into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install CrewAI
pip install crewaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comCustomize the agent
role, goal, and backstory to fit your use caseRun the crew
python crew.py. CrewAI auto-discovers 8 tools from KintoneWhy Use CrewAI with the Kintone MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Kintone 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
Kintone + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Kintone MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Kintone 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 Kintone, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Kintone 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 Kintone against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Example Prompts for Kintone in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Kintone immediately.
"List all apps and show the latest 5 records from the 'Sales Pipeline' app."
"Create a new deal in Sales Pipeline and query all deals over $50K."
"Show the field configuration for the Customer DB app."
Troubleshooting Kintone MCP Server with CrewAI
Common issues when connecting Kintone to CrewAI through Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Kintone + CrewAI FAQ
Common questions about integrating Kintone MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
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?
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?
Can CrewAI agents call multiple MCP tools in parallel?
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)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Explore More MCP Servers
View all →
Coassemble
8 toolsManage online training and LMS via Coassemble — track courses, monitor enrolments, and manage student groups directly from any AI agent.
Customerly
8 toolsCombine live chat, email marketing, and customer surveys in one platform that helps SaaS companies grow and retain users.
Shortcut
7 toolsEquip your AI agent to radically manage your Shortcut workspace. Search stories, track epics and iterations, fetch team members, and audit workflows from your IDE.
Unkey API Management
8 toolsManage and verify your user API keys via Unkey — create, revoke, and track usage directly from any AI agent.