Kachaka MCP Server

Kachaka MCP Server – Bridging Autonomous Robots and AI Assistants

The Kachaka MCP server is a specialized gateway that exposes the full suite of functions and state information from a Kachaka autonomous mobile robot to any AI model that understands the Model Context Protocol (MCP). By acting as a thin translation layer, it allows conversational agents such as Claude, GPT‑4, or local language models to read the robot’s status, control its movements, and process sensory data—all through a unified, declarative API. This solves the long‑standing problem of integrating heterogeneous robotic systems into AI workflows without requiring custom SDKs or proprietary integrations.

At its core, the server implements three logical layers. The resource layer publishes real‑time robot data as MCP resources: position, battery level, current command, map images, and even raw sensor streams like cameras, LiDAR, or IMU readings. The tool layer exposes actionable commands—move to a location, pick up an object, or start/stop navigation—as MCP tools that can be invoked by the AI. Finally, a prompt layer offers high‑level context prompts that automatically embed robot state into the AI’s input, enabling more natural and contextually aware interactions. Together, these layers provide a comprehensive interface that mirrors the robot’s native API while adhering to MCP standards.

Developers benefit from this design in several ways. First, the server abstracts away low‑level networking details; AI models simply send MCP messages and receive structured JSON responses. Second, the built‑in authentication and security layer allows fine‑grained control over who can read or write to the robot, which is essential for production deployments. Third, because the server communicates with Kachaka via gRPC, it guarantees low‑latency, reliable data exchange—a must for real‑time navigation or safety‑critical commands.

Typical use cases include warehouse automation, where an AI assistant can answer questions about inventory locations while simultaneously issuing pick‑and‑place commands; retail environments, where a chatbot can guide customers to products by controlling a robot concierge; or research labs that need to prototype new navigation strategies in natural language. In each scenario, the MCP server eliminates boilerplate code and enables rapid experimentation: a developer can spin up the server once, register it with an AI platform, and immediately start writing prompts that reference or invoke .

Because the server is open source and conforms to MCP’s evolving specifications, it remains future‑proof. New Kachaka features can be added by extending the resource or tool layers, and any MCP‑compliant client—desktop assistants, web apps, or custom scripts—can consume the robot’s capabilities without modification. This combination of flexibility, security, and ease of integration makes Kachaka MCP Server a standout solution for bringing autonomous robots into the conversational AI ecosystem.