Loading ToolBench
MCP server for hardware control integration with Ollama LLM, providing GPIO, camera, audio, and input device management for Raspberry Pi and virtual hardware environments
This server exhibits severe quality gaps across all dimensions. Tool names lack action verbs and fail to disambiguate overlapping functionality. Descriptions are extremely terse (avg 18-30 chars), well below the 194-char baseline and failing to specify WHEN to use each tool or WHAT state changes occur. Input schemas exist but parameters lack descriptions entirely, LLMs cannot infer what 'pin' or 'duration' mean without context. No output schemas are documented. Error handling is absent, no guidance for recovery, retryable vs fatal errors, or actionable messages. The composition is also problematic: virtual_led_control, virtual_button_press, virtual_camera_capture, virtual_audio_play, and virtual_audio_record are superficially different but form a tightly coupled hardware simulator with no clear orchestration patterns. All tools appear to return 'a dictionary with the result', never documented. This is a classic alpha-stage simulator lacking production-grade tool definitions.
Play audio from text using text-to-speech. Args: text: The text to convert to speech Returns: A dictionary with the result of the operation
Record audio from a virtual microphone. Args: duration: Recording duration in seconds Returns: A dictionary with the result of the operation
Simulate a button press on a virtual button. Args: pin: The GPIO pin number duration: The duration of the button press in seconds Returns: A dictionary with the result of the operation
Capture an image from a virtual camera. Returns: A dictionary with the result of the operation
Control a virtual LED. Args: pin: The GPIO pin number state: The desired state ('on', 'off', or 'blink') Returns: A dictionary with the result of the operation
Tool names do not follow verb_noun convention. 'virtual_led_control', 'virtual_button_press', 'virtual_camera_capture' are all prefixed with 'virtual_' (domain qualifier) rather than starting with action verbs like 'set_', 'activate_', 'capture_', 'play_', 'record_'. LLMs rely on verb-noun names to infer intent before reading descriptions.
Descriptions are far below baseline (18-30 chars; baseline 194 chars). All descriptions are trivial: 'Control a virtual LED', 'Simulate a button press', 'Capture an image from a virtual camera'. They lack WHEN to use, prerequisites, state-change semantics, return structure, or disambiguation from similar tools.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 31 | <=2025-11-25 | v2 |
| 2026-03-09 | F | 30 | - | v1 |
Parameters lack descriptions entirely. 'pin', 'state', 'duration', 'text' are named but not explained. 'pin' could mean GPIO pin number, audio pin, or something else. 'state' for LED is ('on', 'off', 'blink') but this is in the docstring, not the schema description. The parameter description field in the JSON schema is empty or missing.
No output schemas documented. All tools claim to return 'A dictionary with the result' but never specify the dictionary structure, field names, types, or example values. Agents cannot plan downstream calls or extract relevant data.
No error handling guidance. No indication of retryable vs fatal errors, no actionable messages for common failures, no hints on how to recover (e.g., 'Invalid pin: use GPIO 17-27'). An LLM hitting an error has no recovery path.
virtual_led_control uses enum 'state' with values ('on', 'off', 'blink') mentioned in docstring but not enforced in schema. The 'state' parameter should declare enum: ['on', 'off', 'blink'] in the JSON Schema.
No idempotency guarantees. If virtual_led_control is called twice with the same pin and state, are both calls safe to retry? If virtual_button_press is retried after a timeout, does the button press twice? Agents need to know.
No tool annotations (readOnlyHint, destructiveHint, idempotentHint). virtual_button_press and virtual_audio_play are state-modifying (WRITE) but this is not signaled in schema. Agents should know which tools are safe to call speculatively.
Tool composition lacks orchestration. Five tightly coupled hardware simulator tools with no clear composition patterns. If an agent wants to 'record audio while the LED blinks', there is no atomic tool for that, it requires manual sequencing and no guarantees of atomicity or transaction semantics.