kintone MCP Server Integration

AI kintone MCP Server Automation

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FlowHunt provides an additional security layer between your internal systems and AI tools, giving you granular control over which tools are accessible from your MCP servers. MCP servers hosted in our infrastructure can be seamlessly integrated with FlowHunt's chatbot as well as popular AI platforms like ChatGPT, Claude, and various AI editors.

What does “kintone” MCP Server do?

The kintone MCP Server is a Model Context Protocol (MCP) server designed for seamless integration between AI assistants and the kintone platform. It enables AI tools—such as Claude Desktop—to explore, query, and manipulate data within kintone applications. By acting as a bridge, the server empowers developers and end-users to automate workflows, manage records, and interact with kintone databases directly through AI-driven prompts. This integration simplifies tasks like retrieving project statuses, updating records, and generating reports, significantly enhancing development and operational workflows by making kintone’s capabilities accessible via natural language and AI agents.

List of Prompts

No explicit prompt templates are documented in the repository.

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List of Resources

No explicit resources are documented in the repository.

List of Tools

No explicit tools are listed in the public documentation or in the available files.

Use Cases of this MCP Server

  • Project Status Tracking
    AI agents can retrieve the latest status updates for specific projects, helping teams stay informed without manually browsing kintone dashboards.

  • Automated Record Updates
    Users can instruct the AI to update fields—such as project progress—across multiple kintone records, streamlining data entry and minimizing errors.

  • Contextual Data Exploration
    The AI can access and summarize information from various kintone apps, making it easier for users to get overviews or specific insights.

  • Reporting and Data Extraction
    AI-driven queries allow for pulling and formatting data from kintone into reports, facilitating quicker decision-making.

How to set it up

Windsurf

No specific instructions or configuration details for Windsurf are provided in the repository.

Claude

  1. Download the Latest Release
    Get the latest version of the kintone MCP Server from the release page .
  2. Place the Executable
    Move the executable to your preferred location.
  3. Edit Configuration File
    Locate and open claude_desktop_config.json:
    • MacOS/Linux: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  4. Add MCP Server Configuration
    Insert the following JSON snippet under the mcpServers section:
    {
      "mcpServers": {
        "kintone": {
          "command": "C:\\path\\to\\mcp-server-kintone.exe",
          "env": {
            "KINTONE_BASE_URL": "https://<domain>.cybozu.com",
            "KINTONE_USERNAME": "<your username>",
            "KINTONE_PASSWORD": "<your password>",
            "KINTONE_API_TOKEN": "<your api token>, <another api token>, ...",
            "KINTONE_ALLOW_APPS": "1, 2, 3, ...",
            "KINTONE_DENY_APPS": "4, 5, ..."
          }
        }
      }
    }
    
  5. Restart Claude Desktop
    Restart the application to apply the changes.

Securing API Keys

Use the env object to securely store sensitive information:

{
  "mcpServers": {
    "kintone": {
      "command": "C:\\path\\to\\mcp-server-kintone.exe",
      "env": {
        "KINTONE_API_TOKEN": "<your api token>"
      }
    }
  }
}

Cursor

No specific instructions or configuration details for Cursor are provided in the repository.

Cline

No specific instructions or configuration details for Cline are provided in the repository.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

FlowHunt MCP flow

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "kintone": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “kintone” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.


Overview

SectionAvailabilityDetails/Notes
Overviewkintone MCP Server bridges AI tools with kintone for data access and manipulation.
List of PromptsNone documented.
List of ResourcesNone documented.
List of ToolsNone documented.
Securing API KeysUses env in configuration JSON.
Sampling Support (less important in evaluation)Not mentioned.

Our opinion

The kintone MCP Server provides clear integration for Claude Desktop, with strong credential management. However, it lacks documentation on prompts, resources, and tool specifics, making it less accessible for advanced use or for integration with other platforms. Its documentation is functional but limited in technical depth for developers. Based on the above, we rate this MCP server a 4/10 for completeness and developer usability.

MCP Score

Has a LICENSE✅ MIT
Has at least one tool
Number of Forks2
Number of Stars11

Frequently asked questions

Integrate kintone with AI using FlowHunt

Empower your AI agents to automate, explore, and manage kintone data with the kintone MCP Server. Start building intelligent flows today.

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