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nUR MCP Server

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get_robot_model

Retrieve the model of a Universal Robot by providing its IP address to identify and manage industrial robot configurations.

Instructions

获取指定IP的机器人型号 IP:机器人地址

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipYes

Implementation Reference

  • The main handler function for the MCP tool 'get_robot_model'. It sends the command to the robot's DashboardClient to get the model and appends 'e-series' indicator if remote control is enabled/disabled.
    @mcp.tool()
    def get_robot_model(ip: str):
        """获取指定IP的机器人型号
        IP:机器人地址"""
        try:
            robot_list[ip].robotConnector.DashboardClient.ur_get_robot_model()
            model = robot_list[ip].robotConnector.DashboardClient.last_respond
            robot_list[ip].robotConnector.DashboardClient.ur_is_remote_control()
            e = robot_list[ip].robotConnector.DashboardClient.last_respond.lower()
            if e == 'true' or e == 'false':
                model = f"{model}e"
            logger.info(f"{model}e")
            return return_msg(model)
        except Exception as e:
            logger.error(f"获取机器人型号失败: {str(e)}")
            return return_msg(f"获取机器人型号失败: {str(e)}")
  • Low-level helper method in DashboardClient that sends the 'get robot model' command to the UR robot's dashboard server (port 29999).
    def ur_get_robot_model(self):
        '''
        Returns the robot model
        '''
        self.__send('get robot model\n')
  • Helper function used by get_robot_model to format the response as JSON.
    def return_msg(txt: str):
        return json.dumps(txt, indent=2, ensure_ascii=False)
  • The FastMCP instance where all @mcp.tool() decorated functions are automatically registered as MCP tools.
    mcp = FastMCP(
        "nUR_MCP_SERVER",
        description="Control UR robots through the Model Context Protocol"
    )
  • The tool schema/arguments described in the docstring: takes 'ip: str' as input.
    """获取指定IP的机器人型号
    IP:机器人地址"""
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It implies a read-only operation but doesn't disclose behavioral traits such as error handling (e.g., invalid IP), response format, latency, or authentication needs. For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded with the core purpose in the first sentence. The second sentence ('IP:机器人地址') is somewhat redundant but adds slight clarification. Overall, it's efficient with minimal waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain what the tool returns (e.g., model string, error codes) or operational context (e.g., requires robot to be online). For a tool in a robotics context with many siblings, more detail is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal semantics: it states the IP parameter is for the robot address. With 0% schema description coverage and 1 parameter, the description compensates slightly by clarifying the parameter's purpose, but it doesn't provide format details (e.g., IPv4, hostname) or constraints. Baseline is 3 due to low schema coverage and partial compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb '获取' (get/retrieve) and the resource '机器人型号' (robot model), specifying it's for a robot at a given IP address. It distinguishes from siblings like get_serial_number or get_ur_software_version by focusing on model identification. However, it doesn't explicitly differentiate from all siblings (e.g., get_robot_mode), so it's not a perfect 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., robot connectivity), exclusions, or comparisons to similar tools like get_serial_number. The agent must infer usage from the name and description alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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