ktalk-mcp

by mainpart

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct resource and action: room creation, meeting creation, meeting listing/detail, recording listing/detail/download, chat retrieval, and auth status. There is no overlap or ambiguity between any two tools.
Naming Consistency4/5
The naming pattern is predominantly verb_noun (create_room, create_meeting, list_meetings, get_meeting, list_recordings, get_recording, download_recording, get_chat_messages). The only outlier is auth_status, which uses a noun_noun form, slightly breaking the otherwise consistent convention.
Tool Count5/5
With 9 tools, the server is well-scoped for its purpose of managing meetings, recordings, rooms, and chat. The count is neither too sparse nor overwhelming, and each tool contributes a distinct capability.
Completeness4/5
The tool set provides solid coverage for creating rooms and meetings, browsing meetings and recordings, downloading recordings, and fetching chat messages. However, there are no update/delete operations for rooms or meetings, and no list/get for rooms, which are minor gaps for full lifecycle management.
Average 4.3/5 across 9 of 9 tools scored. Lowest: 3.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 15 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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  ]
}
```
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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?
Annotations already indicate this is a write operation (readOnlyHint=false) and not idempotent. The description adds only the return value ({url, event}), but an output schema exists, so this is redundant. It does not disclose side effects, permission requirements, or behaviors like duplicate creation on repeated calls.
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, front-loaded sentence that conveys the core purpose and return value. Every word earns its place, with no unnecessary filler.
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?
For a tool with 11 parameters and a rich schema, the description is minimal but the schema and annotations provide sufficient context. The output schema covers return values, so the description need not explain them. It is slightly lean but functionally complete.
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?
Schema description coverage is 100%, so the baseline is 3. The description does not add any information about parameter semantics beyond what the schema already provides, so it neither compensates nor detracts.
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 'Schedule a calendar meeting' uses a specific verb and resource, clearly distinguishing it from sibling tools like create_room (which creates a room) and list_meetings (which lists). It also states what it returns, adding value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied by the name and description, but there is no explicit guidance about when to use this tool versus alternatives, such as 'use create_room if you only need a room without scheduling'. No exclusions or alternative references are provided.
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?
The description explicitly says 'or overwrite', which adds specificity beyond the destructiveHint annotation by revealing that an existing room may be replaced. However, it does not explain the side effects of overwriting, such as what happens to existing settings or participants, and relies on annotations for the core destructive nature.
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 sentence that front-loads the core purpose and includes return information. There is zero fluff or repetition; every word adds value.
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 complexity (8 params, destructive overwrite behavior, output schema), the description is sparse. It does not clarify when overwriting occurs (e.g., based on slug) or the implications of using a slug vs omitting it. The schema covers parameter details, but the description lacks operational context for the overwrite scenario.
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 input schema provides full descriptions for all 8 parameters, including defaults and enums, so the description does not need to add parameter details. The description's mention of return fields is not parameter-related. Baseline of 3 is appropriate given the high schema coverage.
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 action ('Create (or overwrite) a Talk room') with a specific verb and resource, and explicitly mentions the overwrite scope. It also lists the return values, distinguishing it from sibling tools like create_meeting by focusing on a room object.
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 gives no guidance on when to use this tool versus alternatives such as create_meeting or other sibling tools. There is no mention of prerequisites, use cases, or conditions under which overwriting is appropriate.
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?
The description adds a key behavioral detail beyond the annotations: 'An existing file at target_path is overwritten.' This complements the destructiveHint=true annotation by specifying exactly what is destructive. It also mentions 'best available quality,' giving a concrete behavioral expectation. No contradiction with annotations.
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 primary action and followed by the essential overwrite warning. Every word adds value; there is no fluff. This is an excellent example of concise, structured documentation.
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?
For a simple file-download tool, the description covers the core behavior and safety caveat. It could mention what happens when target_path is a directory or potential output formats, but the presence of annotations and output schema fills some gaps. Overall, the description is sufficiently complete for an agent to use the tool correctly in most cases.
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?
Schema description coverage is 100%, so the baseline is 3. The description does not add much beyond the schema, aside from implying overwrite behavior for target_path and quality selection. It does not clarify the file-vs-directory ambiguity present in the schema's target_path description, leaving the parameter semantics adequately but not richly explained.
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 action ('Download a recording's video file to disk') and resource ('recording'), with the added qualifier 'best available quality'. This distinguishes it from siblings like list_recordings and get_recording, which are for listing and retrieving metadata rather than downloading files.
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 tool's purpose is self-evident from the description: use it when you need the actual video file of a recording, as opposed to listing recordings or getting metadata. No explicit exclusions or alternative tool names are given, but the context is clear enough to guide selection.
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?
Annotations already cover read-only, idempotent, and non-destructive behavior, so the description adds extra context beyond them. It explains that a missing field means 'not in this payload' rather than 'no data at all' and describes how anonymous guests appear, providing valuable behavioral detail for handling responses.
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 a single, lengthy paragraph but stays focused on the tool's behavior and data shape. It front-loads the core purpose and then elaborates on field details and edge cases; while a bit verbose, each part contributes useful information without excess fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and that the output schema is not shown (though hinted to exist), the description comprehensively explains the return payload, including field enumeration, missing-field semantics, and anonymous participant representation. It fully prepares the agent to understand what get_meeting returns and how to interpret it.
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?
Schema description coverage is 100%, so the schema already documents each parameter clearly. The description adds extra nuance by explaining that fields are requested 'by key' and that omitted parameters default to all fields, plus the meaning of missing fields, enriching the parameter semantics beyond the schema.
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 'One meeting with its full participant list,' which specifies the verb (get) and resource (meeting), and distinguishes it from list_meetings by focusing on a single meeting. It also explains the default return behavior, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by saying 'One meeting' and referencing the conference_key, but it never explicitly states when to use this tool over siblings like list_meetings or get_recording. No exclusions or alternatives are mentioned, leaving usage guidance implicit rather than explicit.
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?
Annotations already declare readOnlyHint and idempotentHint, and the description adds useful context about what the tool reports and how to perform reauthentication. This goes beyond the structured fields and clarifies the tool's read-only behavior.
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 concise sentences. The first sentence front-loads what the tool reports, and the second provides actionable guidance. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, zero parameters, and presence of an output schema, the description fully covers its purpose and usage. It also provides the relevant reauthentication context, making it complete for an AI agent.
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 zero parameters, so the schema description coverage is 100% and the description correctly states 'No parameters.' The baseline for zero-parameter tools is 4, and the description appropriately acknowledges this.
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 identifies the tool as reporting token status, expiry, token-file path, and README link. It distinguishes this auth-focused tool from sibling meeting/recording tools.
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?
It states explicitly that there are no parameters and provides the action to (re)authenticate by placing a Session token in the token_file. This gives clear context for when to use the tool and what to do if authentication is needed, though it doesn't explicitly name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes beyond annotations: explains that fields the API didn't send are simply missing (open-world behavior), that leaving out has_chat skips an extra conference lookup, and that certain fields are bulky and can be omitted. These are useful non-obvious behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but wordy. It redundantly lists every field that already appears in the schema enum, and the sentence 'detail is asked for by id, and for the detail' is confusing. However, it is front-loaded with the core purpose and contains valuable performance and open-world notes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a get-by-detail tool with a full output schema, the description is very complete. It covers participant list semantics, field filtering, missing-field behavior, conference_key uniqueness, download_url usage, and even performance implications. No critical gaps remain.
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?
Schema coverage is 100%, so parameters are already well-documented. The description adds value by noting that the last four fields are bulky and can be excluded via fields, and by clarifying that participant_fields narrows each participant object.
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 specifies a get-by-id operation returning recording detail including participants. It distinguishes itself from siblings by noting that conference_key is only available on this endpoint and download_url is the best-quality file for download_recording.
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?
It implies when to use this endpoint (e.g., when conference_key is needed, or full participant info) and how download_url relates to download_recording. It does not explicitly mention alternatives like list_recordings for broader queries, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behaviors beyond the annotations: writing files with save_path ('writes <base>.json + <base>.txt'), returning a compact summary instead of messages, and the truncation caveat ('non-empty truncated_channels means those channels hit limit'). These details add significant context about side effects and data completeness, which the annotations do not convey. No contradiction with annotations is present.
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 well-structured and information-dense without being verbose. Each sentence serves a purpose: stating the core function, explaining parameter resolution, describing side effects, and documenting return format with a caveat. It is front-loaded with the main purpose and appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the five parameters, output schema, and annotations, the description is remarkably complete. It explains the return format, the meaning of truncated channels, the save_path file-writing behavior, and the parameter resolution. There are no significant gaps that would hinder an agent from invoking the tool correctly.
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 schema covers 100% of parameters with clear descriptions, so baseline is 3. The description adds extra meaning by explaining the relationship between recording_id and conference_key ('The chat lives on the meeting, not the recording') and the side effect of save_path returning a summary instead of messages. This enriches the parameter understanding beyond the schema descriptions, warranting a 4.
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 retrieves meeting chat across all channels, merged and time-ordered. It identifies the resource (meeting chat) and differentiates from siblings like get_meeting and get_recording by focusing on chat content. The mention of passing conference_key or resolving via recording_id further clarifies its scope.
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 on how to use the tool, explaining the difference between conference_key and recording_id: 'pass conference_key, or a recording_id whose conference_key is resolved.' It also explains the save_path behavior, but it does not explicitly state when to choose this tool over alternatives (e.g., get_meeting or get_recording). This is clear context without explicit exclusions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral context: meetings in progress may appear, the API provides no grand total so has_more is the end signal, and missing fields indicate 'not in payload' rather than absence of data. These go beyond the annotations.
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 relatively long but every sentence earns its place. It is front-loaded with a clear purpose and covers ordering, default fields, timezone, return shape, and edge cases in a structured, non-redundant way.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 optional parameters, an output schema, and comprehensive annotations. The description fills the remaining gaps: pagination semantics, time formatting, in-progress meetings, and handling of missing fields. It is complete for the tool's complexity.
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 schema provides 100% coverage with rich parameter descriptions. The tool description adds value by defining the default row set referenced by the fields parameter and explaining the behavior for participant fields (≤6, with get_meeting for full list). This goes beyond the schema alone.
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 lists past meetings, ordered newest first, and is a deep paginated archive. It distinguishes itself from siblings by mentioning 'full list via get_meeting' for participants, implying list_meetings provides a summarized view.
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 gives clear context for when to use the tool (listing past meetings, pagination, default fields). It explicitly points to get_meeting as the alternative for full participant lists, but does not enumerate exclusions such as 'use create_meeting instead'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds substantial behavioral context beyond the annotations: default row selection, no date window, pagination end-signal semantics (has_more is the only end signal), and the meaning of missing fields. It also explains API limitations like no grand total. These traits are not inferable from readOnlyHint or idempotentHint, making this genuinely transparent.
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 moderately long and information-dense, with every sentence providing value. It front-loads the core purpose and default row, then covers edge behaviors. Slightly more concise phrasing could improve readability, but it avoids fluff and is well organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 optional params) and the presence of an output schema description, the description is thorough: it covers default fields, ordering, pagination, absence of date filter, field omission semantics, and alternatives for full data. It addresses all likely usage questions and edge cases, making it complete for an agent to invoke correctly.
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?
Even though schema coverage is 100%, the description adds meaning to the parameters: it explains the default field set, how fields like description and bulky blobs are available, the performance impact of participant_fields (12.4 KB vs 45.0 KB payloads), and the behavior of query as substring case-insensitive search. This goes well beyond the schema's parameter descriptions.
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 lists recordings, newest first, and specifies the default fields. It differentiates itself from siblings like get_recording and download_recording by focusing on the list operation and pagination behavior, giving it a specific verb and resource.
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?
It explains there is no date filter and recommends narrowing via query and limit, which is implicit usage guidance. It also points to get_recording for full participant lists, showing when to use an alternative. However, it does not explicitly state 'use this instead of list_meetings' or other exclusions, so the guidance is mostly about internal limitations rather than comparisons with all siblings.
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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