MCP Remote Control

by AaronGoldsmith

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.1
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: get_device_info retrieves device metadata, list_apps enumerates available applications, launch_app starts a specific app, power_on turns on the TV, and press_key simulates remote button presses. The descriptions explicitly differentiate their functions, eliminating any ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case: get_device_info, list_apps, launch_app, power_on, and press_key. This uniformity makes the tool set predictable and easy to understand, with no deviations in naming conventions.
Tool Count5/5
With 5 tools, this server is well-scoped for remote control functionality. Each tool serves a specific, essential purpose (device info, app management, power control, and key simulation), and none feel redundant or missing for basic TV operations. The count is appropriate for the domain.
Completeness4/5
The tool set covers core remote control operations effectively, including power management, app launching, and key presses. However, minor gaps exist, such as the lack of a power_off tool (though press_key can simulate PowerOff) and no explicit volume control beyond key presses, which agents can work around but might slightly hinder seamless automation.
Average 3.8/5 across 5 of 5 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Powers on the TV' implies a write/mutation operation but doesn't specify if it requires authentication, has side effects (e.g., wakes from standby), rate limits, or error conditions. This is a significant gap for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no annotations, but has an output schema), the description is minimally adequate. The output schema should cover return values, but the description lacks context on behavior and usage, making it incomplete for a mutation tool despite the structural support.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline for this scenario is 4 as it avoids unnecessary information while matching the schema.
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 'Powers on the TV' clearly states the action (verb: 'Powers on') and target resource ('the TV'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'press_key' which might also affect power state, so it misses full sibling distinction.
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. There's no mention of prerequisites (e.g., TV must be connected), when not to use it, or how it relates to siblings like 'press_key' for power control, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the operation retrieves information and specifies the output format (XML), but doesn't mention whether this requires authentication, has rate limits, what happens if the device is offline, or if this is a read-only operation. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states exactly what the tool does and the output format. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized for a simple retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description provides adequate context. It explains what information is retrieved and the format (XML), which complements the structured data. For a simple retrieval tool, this is reasonably complete, though it could benefit from more behavioral context given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist. Baseline for 0 parameters is 4, as the description correctly focuses on what the tool does rather than non-existent inputs.
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 tool's purpose with a specific verb ('Retrieves') and resource ('basic device information'), including examples of what information is returned (model, software version). It doesn't explicitly differentiate from sibling tools, but the focus on device information distinguishes it from app-related or control tools in the sibling list.
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, timing considerations, or how it relates to sibling tools like 'power_on' or 'list_apps'. The agent must infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It implies a mutation action ('presses') but doesn't disclose behavioral traits like whether this requires the TV to be on, if it's idempotent, or what happens on failure. It adds some context with key examples but lacks operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose in the first sentence and parameter details following in a structured format. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is mostly complete. However, it could improve by addressing usage guidelines and more behavioral context, especially since no annotations are provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% coverage. It explains the parameter's purpose, provides concrete examples of common and special keys, and clarifies the expected format, fully compensating for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('simulates') and resource ('a single button press on the TV remote'), distinguishing it from siblings like get_device_info (information retrieval) or launch_app (application launching).
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?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't clarify if this should be used instead of power_on for turning the TV on/off, or how it relates to launch_app for navigation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the return format ('formatted list of app names and their IDs') and hints at a read-only operation ('Lists'), but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, or how it handles errors. The description adds some value but lacks comprehensive behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by usage context. Every sentence earns its place by adding value (listing resources and explaining output utility), with zero waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no annotations, but with an output schema), the description is mostly complete. It explains what the tool does and how the output is used, but could benefit from more behavioral details (e.g., permissions or error handling) since annotations are absent. The output schema likely covers return values, reducing the need for description here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the inputs. The description doesn't need to add parameter details, but it does provide context about the output's purpose. Baseline for 0 params is 4, as it compensates adequately without redundant information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lists') and resource ('all available apps and their corresponding Roku channel IDs'), and distinguishes this from siblings like launch_app (which uses the IDs) and get_device_info (which returns device status). It specifies both what it returns and how the output can be used.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the output ('can be used with launch_app()'), providing clear context for its purpose. However, it doesn't specify when NOT to use it or mention alternatives among siblings (e.g., whether get_device_info might also list apps).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that app_name is case-insensitive, which is useful context beyond the basic action. However, it doesn't cover other behavioral aspects like error handling (e.g., what happens if the app isn't installed), permissions needed, or side effects (e.g., does it change TV state).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose in the first sentence and parameter details in a structured Args section. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is mostly complete. It covers the purpose, parameter semantics, and basic usage. However, it could improve by addressing behavioral aspects like error cases or prerequisites, especially since no annotations are provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that app_name is the name of the app to launch, provides examples (Netflix, YouTube, Hulu), specifies it's case-insensitive, and references list_apps() for available options, fully compensating for the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Launches an application') and resource ('on the TV'), distinguishing it from siblings like list_apps (which lists apps) or press_key (which simulates key presses). It precisely defines what the tool does without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (to launch an app by name) and references list_apps() as a way to see available apps, offering implicit guidance. However, it doesn't explicitly state when not to use it or compare it to alternatives like power_on for broader device control.
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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