Kachaka MCP サーバー

@comoc

Basic information

About Kachaka MCP サーバー

Kachaka MCP Server - Model Context Protocol server for Kachaka robot

Kachaka MCP サーバー config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "kachaka-mcp": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

Kachaka MCP サーバー tools

Tool list not available yet

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Kachaka MCP サーバー?

Kachaka MCP サーバー is an experimental server that provides Kachaka robot’s functionality to various AI models through the Model Context Protocol (MCP). It enables AI models such as Claude, GPT-4, and local LLMs to understand and control Kachaka’s state.

How to use Kachaka MCP サーバー?

Install the server with uv sync after cloning the repository. Configure the server by setting the environment variable KACHAKA_HOST to your Kachaka host address or by creating a config file at ~/.kachaka-mcp/config.json. Run the server with uv run python -m kachaka_mcp.server or use mcp run kachaka_mcp.server; for Claude Desktop, add the server configuration to claude_desktop_config.json.

Key features of Kachaka MCP サーバー

Exposes robot status, map, and sensor data as MCP resources.
Provides movement, shelf, system, and map operation tools.
Offers prompt templates for AI interaction and error handling.
Supports API key-based authentication and access control.
Uses gRPC to communicate with the Kachaka API client.

Use cases of Kachaka MCP サーバー

An AI assistant commands the robot to move to a named location.
A user asks the AI to dock or undock the robot from a shelf.
The AI retrieves the robot’s battery level and current command state.
A map is switched or exported remotely via an AI chat interface.
The robot speaks a text message when prompted by an AI model.

Frequently asked questions

What are the runtime dependencies?

Python >=3.10, and packages including `mcp[cli]>=1.7.1`, `kachaka-api`, `grpcio`, `pydantic`, `pillow`, `numpy`, `loguru`, and `protobuf==5.27.2`.

How do I configure the server?

Set the environment variable `KACHAKA_HOST` to the Kachaka host address, or place a JSON config file at `~/.kachaka-mcp/config.json` (Linux/macOS) or `%USERPROFILE%\.kachaka-mcp\config.json` (Windows). The config location can be overridden with `KACHAKA_MCP_CONFIG`.

Does the server support authentication?

Yes, it provides API key-based authentication, access control, and operation logging through a dedicated authentication and security layer.

Is this server ready for production use?

No, the code is currently experimental and may not work correctly. Use with caution.

Comments

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