Overview

The Chatwork MCP Server is a lightweight bridge that lets AI assistants—such as Claude Desktop—interact directly with the Chatwork collaboration platform. By exposing a Model Context Protocol (MCP) interface, it translates standard MCP commands into authenticated Chatwork API calls. This allows developers to embed real‑time chat, task management, and file sharing into AI workflows without writing custom integrations for each platform.

What Problem It Solves

Modern teams rely on chat‑centric tools like Chatwork to coordinate tasks, share documents, and hold asynchronous conversations. AI assistants often lack native support for these services, forcing developers to build custom connectors or rely on generic webhooks. The Chatwork MCP Server eliminates that friction by providing a ready‑made, secure entry point: once the server is running and configured with an API token, any MCP‑compliant client can send commands such as “post a message”, “create a task”, or “list recent files” and receive structured responses. This removes the need for repetitive authentication logic, rate‑limit handling, or data mapping.

Core Functionality and Value

At its heart, the server listens for MCP requests over a local command line interface (invoked via ). It accepts a configuration that specifies the Chatwork API token, then translates generic MCP actions into HTTP requests to Chatwork’s REST endpoints. The result is a seamless, typed conversation between an AI model and the chat platform—messages can be sent to rooms, tasks created with due dates, or file attachments retrieved—all through the same prompt‑based interface that developers already use for other tools.

Developers benefit from:

• Zero‑code integration: No custom SDKs or HTTP client logic are required.
• Secure token handling: The server reads the token from environment variables, keeping credentials out of code and configuration files.
• Consistency across tools: Because it follows the MCP standard, the same AI client can interact with Chatwork alongside other services (e.g., GitHub, Jira) using identical command patterns.

Key Features Explained

• Command‑line launcher: The server is started via a simple command, making it trivial to add to existing development workflows or CI pipelines.
• Environment‑based authentication: By pulling the from the environment, developers can keep secrets safe and switch contexts easily.
• Rich resource support: Messages, tasks, rooms, and files are exposed as MCP resources, allowing complex interactions such as querying a room’s message history or updating a task status.
• Extensible configuration: The MCP server is defined in the client’s , enabling quick toggling or scaling to multiple servers.

Real‑World Use Cases

1. Automated Meeting Summaries
   An AI assistant can monitor a Chatwork room, pull the latest messages after a meeting, and generate a concise summary that’s posted back to the same room.

2. Task Management Automation
   When a user prompts “Create a new task for the marketing team”, the assistant creates a Chatwork task with due dates and assignees, eliminating manual clicks.

3. File Retrieval in Conversational AI
   A user can ask the assistant to “Show me the latest design file”, and the server returns a direct link or attachment from Chatwork, streamlining collaboration.

4. Cross‑Platform Notifications
   Integrate the server into a larger MCP ecosystem so that an AI can post alerts to Chatwork whenever a GitHub PR is merged or a Jira issue changes state.

Integration with AI Workflows

Because the server follows the MCP specification, any AI platform that supports MCP can treat Chatwork as just another tool. Developers simply add the server to their configuration, and the AI can issue commands like , , or in a prompt. The server handles authentication, error translation, and response formatting, allowing the AI to focus on higher‑level reasoning rather than plumbing details. This tight coupling simplifies pipeline construction, reduces boilerplate, and accelerates time‑to‑value for AI‑powered collaboration solutions.