How to Use the Kintone MCP in AutoGen

Q: Does AutoGen support Kintone space lookups?

Yes. Use the listspacemembers tool to allow your agents to identify stakeholders for specific projects or apps within your Kintone space.

Let your AutoGen agents debate and execute Kintone tasks through consensus-driven tool calls.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Kintone MCP to AutoGen

Create your Vinkius account to connect Kintone to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Kintone with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Consensus-based Kintone record management

Enable multiple agents to debate the validity of a Kintone update. One agent proposes a change via `add_record`, while another checks the data against business rules. This ensures that only verified information enters your system. The agents negotiate the final state of the record, reducing errors in your business data.

Multi-agent app administration

Task agents with exploring your Kintone environment. They use `list_apps` and `get_app_details` to map out the available data, then decide which app requires attention. This collaborative approach handles complex workflows. Agents work together to identify the correct target app before executing any read or write commands.

Deliberative Kintone data workflows

Run agents that negotiate data cleanup tasks. When an agent suggests `delete_records`, another agent can challenge that decision based on existing dependencies. This process adds a layer of human-like oversight to your automation. The agents converge on an action only after evaluating the impact on your Kintone records.

Setup guide

Set up Kintone MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Kintone tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Kintone_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Kintone data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Kintone_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Kintone data")
    print(result.messages[-1].content)

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 Kintone. 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 Kintone 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 Kintone MCP in AutoGen

Use the autogen-ext package to fetch tools from your server. Pass the resulting list directly into your AssistantAgent constructor to enable Kintone access.

Yes. Since agents operate in the same conversation, they can pass data retrieved via `list_records` from one agent to another for further evaluation.

Tools are treated as actions the agents can propose. Other agents can critique the tool call arguments, such as the JSON payload for `add_record`, before execution.

Yes. Use the `list_space_members` tool to allow your agents to identify stakeholders for specific projects or apps within your Kintone space.

Access is restricted by your endpoint token. Each agent interaction is logged for auditability, and no data is shared with other external services.

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