Server Quality Checklist
- Disambiguation4/5
Tools are well-distinguished with clear descriptions differentiating URL-based casting (tv_cast), name-based playback (tv_play), and ID-based launching (tv_launch). Minor overlap exists between tv_audio (multi-room music volume) and tv_volume (single TV volume), but scopes differ sufficiently.
Naming Consistency4/5Most tools follow the tv_<word> pattern consistently. Minor deviations include tv_list_tvs (compound noun breaking the single-word pattern) and tv_whats_on (informal phrase), but the prefix convention remains readable throughout.
Tool Count3/5With 21 tools, the set is comprehensive but approaches the upper limit of manageable scope. While each tool serves a distinct function (power, casting, queuing, insights, scenes), the breadth borders on overwhelming for an agent selecting from the full set.
Completeness4/5Covers the full TV control lifecycle well: power, volume, content playback via multiple methods, queue management, status checks, and analytics. Minor gaps exist in group/scene management (read-only/listing only, no creation or editing tools).
Average 3.8/5 across 21 of 21 tools scored. Lowest: 2.3/5.
See the tool scores section below for per-tool breakdowns.
This repository includes a README.md file.
This repository includes a LICENSE file.
Latest release: v0.1.0
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
- This server provides 21 tools. View schema
No known security issues or vulnerabilities reported.
This server has been verified by its author.
Add related servers to improve discoverability.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only adds 'recent' without defining timeframe, scope, or volume of records returned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely brief (3 words) but lacks information density; front-loaded but insufficient content to evaluate structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Marginally adequate given low complexity and existing output schema, but critical gaps remain around parameter purpose and history scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage and description fails to compensate—no mention of what 'limit' controls or its default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
States basic function (show play history) but 'recent' is vague and doesn't differentiate from siblings like tv_whats_on or tv_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this versus tv_status, tv_whats_on, or tv_insights.
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?
Discloses asyncio.gather execution model and 'resolves once' timing, but lacks error handling semantics (fail-fast vs partial success) or state requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded purpose statement followed by behavioral note and structured Args section; no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic invocation given output schema exists, but omits error handling, network requirements, and TV state prerequisites.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Comprehensively documents all 7 parameters with valid values (e.g., platform enums) and relationships (tv_names vs group), compensating for 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states multi-TV playback with 'simultaneously' and 'party mode' distinguishing it from single-TV siblings like tv_play, though could explicitly mention synchronization behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use versus tv_play/tv_launch for single TVs, or when to prefer tv_names vs group parameters.
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?
Discloses default behaviors (omit platform for both, default 10 results) but lacks information on rate limits, data freshness, or authentication requirements given no annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Appropriately brief with clear Args section structure; information is front-loaded though informal formatting.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple 2-parameter tool with output schema; covers all inputs though brief mention of return structure would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Compensates for 0% schema description coverage by documenting valid enum values for platform and precise semantics for limit (results per platform, default 10).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific action (Show trending content) and target platforms (Netflix/YouTube), distinguishing it from sibling control tools like tv_play or tv_volume, though 'content' could specify movies/shows/videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to select this over similar discovery tools like tv_recommend or tv_launch; only documents parameter usage.
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?
Lacks annotations so carries full burden; mentions 'members' are included but omits side effects, caching, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single front-loaded sentence with no redundancy; appropriate length for parameterless tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for low complexity with output schema handling return details, though could clarify what defines a 'TV group'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters present, meeting baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb ('List') and resource ('TV groups and their members'), though lacks explicit contrast with sibling tv_list_tvs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use versus alternatives like tv_list_tvs or tv_insights.
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?
Describes conceptual return types (insights, analysis) but omits operational details like caching, rate limits, or computation methodology since no annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with purpose front-loaded, followed by Args and Examples sections; no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers the complex report_type syntax not captured in schema; omits mention of default values but output schema handles return value documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Effectively compensates for 0% schema description coverage by documenting valid enum values and critical colon-delimited syntax for sub_value reports.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific actions (get viewing insights, screen time, subscription value analysis) but lacks explicit differentiation from sibling tv_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides usage examples but no guidance on when to use this tool versus alternatives like tv_history or tv_recommend.
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?
Explains the boolean mapping (True=on, False=off) but lacks disclosure of side effects, error conditions, or timing behavior given no annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Appropriately brief with no redundant text; front-loaded action statement followed by structured Args section.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Sufficient for the tool's low complexity (2 simple params); appropriately omits return value explanation since output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Effectively compensates for 0% schema description coverage by clearly explaining both parameters' semantics and default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the specific action (turn on/off) and target resource (TV), though it doesn't explicitly differentiate from sibling tools like tv_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus alternatives (e.g., when to check tv_status first or handle already-on states).
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?
Discloses key non-behavior (does not play content) but lacks other traits like error handling, idempotency, or side effects; no annotations to contradict.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with Args/Returns sections; front-loaded purpose followed by param details; no redundant filler though schema repetition could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic invocation but omits error scenarios, parameter relationships (query vs title_id interdependency), and return value format details despite output schema existing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Compensates effectively for 0% schema coverage by documenting all 5 parameters, including platform values and Netflix-specific constraints for optional fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific action (resolve to platform ID) and distinguishes from siblings via 'without playing' clause, though could explicitly name sibling tools it differs from.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides implied guidance via 'without playing' but lacks explicit when-to-use vs alternatives (tv_play, tv_cast) or workflow integration guidance.
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, description carries burden by mentioning built-in scenes exist, but omits side effects, idempotency, or what scene activation actually modifies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear Args/Examples sections; front-loaded purpose sentence makes efficient use of space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic invocation but lacks explanation of what scenes entail (which settings are affected) despite having output schema available.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Compensates well for 0% schema coverage by documenting parameter meanings and conditional requirements (name required for 'run').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific actions (run/list) and resource (scene presets) with built-in examples, distinguishing it from sibling TV control tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides implied usage through examples showing list vs run patterns, but lacks explicit when/when-not guidance or comparison to alternatives like tv_power.
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?
Discloses 'screens off' mode but fails to explain behavioral interactions with overlapping sibling tools or side effects on 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (summary, args, examples); front-loaded purpose statement; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all parameters and provides examples, but critically omits sibling tool relationships needed given the tv_play/tv_volume overlaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Excellent compensation for 0% schema coverage: documents all 6 parameters including constraints (e.g., room vs rooms distinction, platform enum values).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific purpose (multi-room audio with screens off) but doesn't clarify differentiation from sibling tools tv_play and tv_volume.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs tv_play (overlap on 'play') or tv_volume (overlap on 'volume' action), creating agent confusion.
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?
Discloses data sources (watch history + trending) but lacks details on caching, real-time vs. stale data, or whether recommendations update immediately after viewing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded purpose statement followed by Args section; appropriately terse for a simple tool, though formatting is slightly informal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for the tool's simplicity given output schema exists; covers the 'how it works' and parameters, though could mention return type (shows vs. movies).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Excellent compensation for 0% schema description coverage by documenting valid mood values ('chill', 'action', etc.) and limit semantics with defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it gets personalized recommendations using watch history and trending data, distinguishing it from playback/control siblings, though it assumes 'TV content' is understood from the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this versus discovery alternatives like tv_whats_on or tv_history, nor when to omit parameters.
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?
Discloses watch history continuation behavior and Netflix-specific defaulting, but omits error handling (what if no next episode?) and side effects beyond what annotations would provide (none exist).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with front-loaded action statement; Args section is structured and every line provides necessary constraint or default information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers the simple 'next episode' use case given output schema exists; parameter defaults are explained, though edge cases (series completion, offline TV) are unmentioned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Effectively compensates for 0% schema description coverage by defining 'Show name' and 'Target TV name' semantics, plus default behaviors when parameters are null.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific action (play next episode) and distinguishes from generic playback via 'Continues from watch history', though could clarify distinction from tv_play more explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear parameter omission guidance ('Omit to continue...', 'Omit for default TV') but lacks explicit when-to-use guidance versus sibling tools like tv_play or tv_launch.
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?
Discloses what data is returned (compensating for missing annotations), but omits other behavioral traits like idempotency, caching, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, front-loaded with purpose, and uses standard Args format with no redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple read-only query tool; lists output fields even though output schema exists, providing sufficient context for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Effectively compensates for 0% schema description coverage by explaining tv_name semantics ('Target TV name') and default behavior ('Omit for default TV').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Get' with specific resource 'TV status' and enumerates returned fields (app, volume, mute, model, firmware), implicitly distinguishing from sibling control tools like tv_volume or tv_power.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides parameter usage guidance ('Omit for default TV') but lacks explicit guidance on when to select this tool versus siblings (e.g., when to query status vs. directly control).
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?
Reveals internal behavior ('stv parses the platform and content ID automatically') but omits error handling, side effects, or prerequisites given no annotations exist to cover these.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with Args and Examples sections; front-loaded purpose followed by concrete usage patterns, though 'Paste any streaming URL' slightly redundantly reinforces the initial sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers the simple 2-parameter operation; presence of output schema excuses lack of return value documentation, though error scenarios (invalid URL, offline TV) remain unaddressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Fully compensates for 0% schema description coverage by explicitly defining both parameters ('Any Netflix, YouTube, or Spotify URL' and 'Target TV name. Omit for default TV').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb ('Cast') and resource ('URL to the TV'), with specific platform examples (Netflix/YouTube/Spotify) that distinguish it from generic siblings like tv_play, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides implicit guidance through examples and notes the default TV behavior, but lacks explicit when-to-use/when-not-to-use guidance versus alternatives like tv_play or tv_launch.
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?
Specifies 'toast' implying transient display, but lacks details on duration, visibility during playback, or error behaviors (no annotations to supplement).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with front-loaded purpose statement and clear Args section; no redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Minimum viable for a 2-parameter tool; misses behavioral nuances (interruption level, persistence) that would help distinguish from tv_screen or tv_display given the large sibling set.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Compensates perfectly for 0% schema coverage by defining both parameters: 'Text to display' and 'Target TV name. Omit for default TV.'
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'Show' + resource 'toast notification' clearly distinguishes this from sibling media/control tools like tv_play or tv_power.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use versus alternatives (e.g., tv_screen for persistent messages) or when notifications are appropriate.
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, description carries burden but only explains basic actions; omits side effects (does 'clear' stop current playback?, is 'play' immediate?) and error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Excellent structure with clear sections (summary, Args, Examples); front-loaded purpose with no redundancy; examples demonstrate real usage patterns efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters with conditional logic and presence of output schema, covers all inputs adequately; minor gap in explaining 'skip' behavior precisely (current vs next item).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, comprehensively compensates by detailing every parameter's purpose, conditional requirements, and valid values inline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific verb ('Manage') and resource ('play queue'), and distinguishes from siblings by focusing on queue operations (add/show/clear) rather than direct playback.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Documents conditional requirements (e.g., platform required for 'add') but lacks explicit guidance on when to use queue vs direct playback tools like tv_play or tv_launch.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries burden by disclosing return fields (name, platform, IP, default status); omits side effects (none) but sufficient for read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single front-loaded sentence with zero fluff; every clause earns its place by specifying scope or output fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for low complexity (no params, output schema exists); mentions key return fields though could note this is read-only/discovery.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters per schema; baseline 4 applies, no parameter explanation needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'List' with clear resource 'configured TVs' and distinguishes from siblings by enumerating output fields (IP, platform) that discovery tools return.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when/when-not guidance, but implied as discovery tool; misses opportunity to state 'use first before tv_power/tv_cast' given 19 sibling tools.
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?
Explains the resolution and deep-linking flow but omits side effects (e.g., does it interrupt current playback?), error handling, or authentication requirements given no annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded purpose statement followed by mechanism explanation, structured Args list, and concrete Python-style examples that efficiently demonstrate parameter combinations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers 6-parameter complexity with platform-specific logic and examples; output schema exists so return values need not be described, though error scenarios are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Fully compensates for 0% schema description coverage by documenting all parameters inline: platform values, query format, Netflix-specific constraints for season/episode, and title_id optimization.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states 'Find content by name and play it on TV' with specific mechanism (resolves ID, deep-links), and distinguishes itself as 'the primary tool' among siblings like tv_cast, tv_launch, and tv_resolve.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Declares itself 'the primary tool' establishing default usage, and contrasts with tv_resolve by noting automatic ID resolution, though lacks explicit 'when not to use' exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behavioral trait (audio persists when screen off) beyond empty annotations, though omits other potential behaviors like transition effects or latency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely efficient: front-loaded purpose statement followed by concise Args documentation with no extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for low complexity (2 simple params) and presence of output schema; minor gap in not explicitly contrasting with tv_power sibling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Fully compensates for 0% schema description coverage by clearly defining both parameters including boolean semantics and default TV selection behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Specific action (turn screen on/off) clearly stated and distinguished from tv_power via explicit note that audio continues when screen is off.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage context (audio continues) allowing inference of when to use vs tv_power, but lacks explicit when/ when-not guidance or alternative mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses critical implementation detail (local HTML server on specified port) not inferable from schema, though omits whether this interrupts existing TV sessions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear Args/Examples sections; examples are verbose but essential given the unstructured 'anyOf' data schema, making every sentence earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully complete given presence of output schema and complex polymorphic data parameter which is thoroughly explained with concrete examples for each content type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Completely compensates for 0% schema description coverage by exhaustively documenting content_type options, data payload shapes per type, and default behaviors for optional params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Opens with specific action ('Turn the TV into a display') and clearly distinguishes from media-playing siblings (tv_play, tv_cast) by emphasizing dashboards, HTML generation, and browser-based display.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies clear usage context through content examples (dashboards vs. video), though lacks explicit 'when not to use' comparisons to tv_cast or tv_play.
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?
Mentions deep linking capability but lacks disclosure of side effects (e.g., power state changes, app switching behavior) given no annotations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose, followed by usage guidelines and structured Args section; no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for input usage and sibling differentiation; omits behavioral edge cases but output schema exists to cover return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Fully compensates for 0% schema description coverage by documenting all three parameters with clear semantics and examples (netflix, youtube, spotify).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States specific action ('Launch an app') and explicitly distinguishes from sibling tv_play by contrasting content ID vs content name usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when/when-not guidance ('Use tv_play instead if you have a content name... Use this when you already have the exact content ID').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behaviors not in schema: no args returns current status, None toggles mute, and implicitly that operations are atomic (get/set in one tool).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded purpose statement followed by bulleted usage patterns and structured Args section; no redundancy, every line provides actionable guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete coverage of all 4 parameters including tv_name default behavior; defers return value details to existing output schema appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Perfectly compensates for 0% schema description coverage by defining ranges (0-100), valid strings ('up'/'down'), and tristate logic (True/False/None) for mute.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Specific verbs (get, set, step, toggle) with clear resource (volume), and 'All in one' phrasing distinguishes consolidated volume control from sibling tools like tv_audio or tv_power.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Excellent explicit examples showing when to use each parameter combination (no args, level, direction, mute), though lacks explicit mention of alternatives/when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
How to claim the server?
If you are the author of the server, you simply need to authenticate using GitHub.
However, if the MCP server belongs to an organization, you need to first add glama.json to the root of your repository.
{
"$schema": "https://glama.ai/mcp/schemas/server.json",
"maintainers": [
"your-github-username"
]
}Then, authenticate using GitHub.
Browse examples.
How to make a release?
A "release" on Glama is not the same as a GitHub release. To create a Glama release:
- Claim the server if you haven't already.
- Go to the Dockerfile admin page, configure the build spec, and click Deploy.
- Once the build test succeeds, click Make Release, enter a version, and publish.
This process allows Glama to run security checks on your server and enables users to deploy it.
How to add a LICENSE?
Please follow the instructions in the GitHub documentation.
Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear on the server after some time, you can manually trigger a new scan using the MCP server admin interface.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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.