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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
configNoOptional parameter to specify the configuration file name. For example, 'Pico' will load 'Pico_config.yaml'. If not provided, the server defaults to 'config.yaml'.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
set_pwmC

设置PWM频率,范围0-100

get_pico_infoC

获取Pico开发板信息

led_controlC

控制LED开关

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.2/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: get_pico_info retrieves board information, led_control handles LED on/off states, and set_pwm manages PWM frequency settings. There is no overlap or ambiguity between these functions, making tool selection straightforward for an agent.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with clear verb_noun structures: get_pico_info, led_control, and set_pwm. This uniformity enhances readability and predictability across the tool set.

Tool Count4/5

With only 3 tools, the set is minimal but reasonable for controlling a Pico board, covering basic operations like info retrieval, LED control, and PWM settings. It might feel slightly thin for broader IoT tasks, but it aligns well with the apparent scope.

Completeness3/5

The tools cover core functions for Pico board interaction, but there are notable gaps such as missing read operations for LED or PWM states, and no update or delete capabilities. This could limit agent workflows that require full lifecycle management.