Convo

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose with no overlap; for example, 'get_summary' provides key points and decisions, while 'find_action_items' extracts tasks across meetings, and 'ask_about_meeting' allows specific queries. The descriptions clearly differentiate each tool's function, preventing misselection.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as 'get_summary', 'list_meetings', and 'draft_followup_email'. This predictability makes it easy for agents to understand and use the toolset without confusion.
Tool Count5/5
With 12 tools, the server is well-scoped for managing meetings, covering operations from preparation to follow-up. Each tool earns its place by addressing specific aspects like transcription, summarization, action tracking, and integration with calendars.
Completeness5/5
The toolset provides complete CRUD/lifecycle coverage for meeting management: listing and getting meetings, preparing, summarizing, extracting action items, drafting follow-ups, sharing, and generating digests. No obvious gaps exist, ensuring agents can handle end-to-end workflows without dead ends.
Average 3.2/5 across 12 of 12 tools scored.
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 status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

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.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that 'The AI will answer based on the transcript,' which hints at the tool's reliance on transcript data, but doesn't cover critical aspects like response format, error handling, rate limits, authentication needs, or whether it's read-only or mutative. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 extremely concise and front-loaded, consisting of two clear sentences that directly state the tool's purpose and mechanism. There's no wasted language or redundancy, making it easy for an agent to parse quickly. Every sentence earns its place by providing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a Q&A tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., how answers are generated, limitations), output format, and usage guidelines. While it states the basic purpose, it doesn't provide enough context for an agent to fully understand how to invoke it effectively or interpret results, especially compared to sibling tools.
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%, with both parameters ('meeting_id' and 'question') well-documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides (e.g., it doesn't explain format constraints for 'meeting_id' or examples for 'question'). Given the high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.
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: 'Ask any question about a specific meeting. The AI will answer based on the transcript.' It specifies the verb ('ask any question'), resource ('specific meeting'), and mechanism ('based on the transcript'). However, it doesn't explicitly distinguish this from sibling tools like 'get_summary' or 'get_transcript' which might provide similar meeting information, so it doesn't reach the highest score.
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 when-not scenarios, prerequisites, or compare it to sibling tools such as 'get_summary' (for summaries) or 'get_transcript' (for raw transcripts). The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.
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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool drafts emails and references discussion points, but lacks critical details: whether it generates editable drafts or final sends, what permissions or data access are needed, how it handles missing information, or any rate limits. For a tool that likely accesses meeting data and creates content, this is insufficient transparency.
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 extremely concise at just two short sentences, with zero wasted words. It's front-loaded with the core purpose ('Draft a follow-up email based on a meeting') and adds only essential context ('References actual discussion points'). Every sentence earns its place by clarifying scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a tool that creates content based on meeting data, the description is incomplete. It doesn't explain what the output looks like (e.g., email text, subject line), how meeting points are referenced, or behavioral constraints. For a 3-parameter tool with potential complexity in email generation, more context is needed.
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 schema fully documents parameters (meeting_id, recipient_name, tone with enum). The description adds no additional parameter semantics beyond implying 'meeting_id' links to discussion points. With high schema coverage, the baseline is 3 even without param details in the description.
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: 'Draft a follow-up email based on a meeting' with the specific action 'draft' and resource 'follow-up email'. It distinguishes from siblings like 'get_summary' or 'get_transcript' by focusing on email creation rather than information retrieval. However, it doesn't explicitly differentiate from all siblings (e.g., 'weekly_digest' might also involve email generation).
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 (e.g., needing a meeting transcript), exclusions (e.g., not for initial outreach), or comparisons with siblings like 'share_meeting' (which might involve email sharing). The phrase 'References actual discussion points' hints at context but doesn't constitute explicit usage guidelines.
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 but offers minimal behavioral context. It states what content is returned (speaker names, timestamps) but doesn't disclose permissions needed, rate limits, error conditions, format of the transcript (e.g., structured vs plain text), or whether it's a read-only operation. For a tool with zero annotation coverage, this is inadequate.
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 front-loads the core purpose. Every word earns its place by specifying the action, resource, and key content details. There is no redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple input schema, the description is incomplete. It lacks critical context such as the return format (e.g., JSON structure, text), error handling, authentication requirements, or limitations. For a tool that retrieves meeting data, more behavioral details are needed to ensure proper agent usage.
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% (meeting_id is fully described in schema), so the baseline is 3. The description adds no parameter-specific information beyond what the schema provides (e.g., no examples of meeting_id format, no constraints). It meets the minimum viable level given high schema coverage.
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 verb 'Get' and resource 'full transcript of a meeting', specifying the content includes 'speaker names and timestamps'. It distinguishes from siblings like get_summary (summary vs full transcript) and list_meetings (list vs get specific transcript). However, it doesn't explicitly differentiate from all siblings (e.g., ask_about_meeting might also involve transcripts).
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 (e.g., needing a meeting_id), when not to use it (e.g., for summaries use get_summary), or compare to similar tools like ask_about_meeting. Usage is implied by the purpose but not explicitly stated.
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 the full burden of behavioral disclosure. It states the tool retrieves upcoming meetings but fails to mention critical details like authentication requirements, rate limits, time range defaults, or response format. This leaves significant gaps in understanding how the tool behaves.
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 directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized, making it easy to understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like authentication, time ranges, or response structure, which are crucial for a tool interacting with an external service like Google Calendar. This leaves the agent with insufficient context for effective use.
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 has 100% description coverage, with 'max_results' clearly documented, so the description adds no additional parameter information. The baseline score of 3 is appropriate as the schema handles the parameter semantics adequately, but the description doesn't enhance it.
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 action ('Get') and resource ('upcoming meetings from your connected Google Calendar'), making the purpose evident. However, it doesn't differentiate from sibling tools like 'list_meetings', which might have overlapping functionality, preventing a perfect score.
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 such as 'list_meetings' or other meeting-related tools. It lacks explicit context, prerequisites, or exclusions, offering minimal usage direction.
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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('Generate a shareable link') but doesn't clarify whether this is a read-only operation, if it requires specific permissions, what format the link takes, or if there are rate limits. For a tool that likely involves access control, this leaves significant gaps in understanding its 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 a single, clear sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it efficient and easy to parse. Every part of the sentence earns its place by conveying essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that generates shareable links. It doesn't explain what the link provides (e.g., read-only access, edit permissions), how long it lasts, or what the return value looks like. For a tool with potential security implications, more context is needed to use it effectively.
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 has 100% description coverage, with the single parameter 'meeting_id' documented as 'The meeting/conversation ID'. The description adds no additional parameter context beyond what the schema provides, such as format examples or sourcing guidance. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.
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 action ('Generate a shareable link') and resource ('for a meeting'), making the purpose immediately understandable. It distinguishes itself from siblings like 'get_transcript' or 'list_meetings' by focusing on link generation rather than retrieval or listing. However, it doesn't explicitly differentiate from all siblings (e.g., 'ask_about_meeting' might also involve meeting access), keeping it at 4 instead of 5.
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 (e.g., needing an existing meeting), exclusions (e.g., not for creating meetings), or comparisons to siblings like 'get_transcript' (which might also provide access). Without any usage context, the agent must infer when this tool is appropriate.
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?
No annotations are provided, so the description carries the full burden. It mentions listing recent meetings with search/filter capabilities but fails to disclose critical behavioral traits such as whether it's read-only, requires authentication, has rate limits, or what the return format looks like (e.g., pagination, default sorting). This is a significant gap for a tool with no 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 highly concise and front-loaded, consisting of two short sentences that directly state the tool's purpose and key functionalities. Every word earns its place with no wasted information, making it easy for an agent to quickly understand the tool's scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It covers basic purpose and parameters but misses essential context like behavioral traits (e.g., safety, permissions), return values, and detailed usage scenarios. For a tool with no structured support, this leaves significant gaps for an agent to invoke it correctly.
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%, with each parameter ('limit', 'search', 'since') well-documented in the schema. The description adds minimal value beyond the schema by mentioning 'Search by title or filter by date,' which aligns with the schema but doesn't provide additional syntax or format details. Baseline 3 is appropriate when the schema does the heavy lifting.
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 specific verbs ('List', 'Search', 'filter') and resource ('your recent meetings'). It distinguishes itself from siblings like 'get_upcoming_meetings' by focusing on recent meetings rather than future ones. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_summary' might also involve listing).
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 context through 'Search by title or filter by date,' suggesting when to use it for specific queries. However, it lacks explicit guidance on when to choose this tool over alternatives like 'get_upcoming_meetings' for future meetings or 'get_summary' for summarized lists. No exclusions or prerequisites are mentioned.
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?
No annotations are provided, so the description carries the full burden. It discloses that summaries are generated automatically if not available, which is a useful behavioral trait. However, it doesn't cover other aspects like performance (e.g., latency for generation), error handling, or output format, leaving gaps for a tool that might involve processing.
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 very concise and front-loaded: it states the core purpose in the first clause and adds a key behavioral note in the second. Both sentences earn their place by providing essential information without redundancy, making it efficient and well-structured.
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?
For a tool with one parameter and no output schema, the description covers the basic purpose and a key behavior (automatic generation). However, it lacks details on output format, error cases, or integration with siblings, which could be helpful given the complexity of summary generation. It's adequate but has clear gaps.
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 schema description coverage is 100%, with the single parameter 'meeting_id' well-documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides, such as format examples or constraints. Given high schema coverage, the baseline score of 3 is appropriate.
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: 'Get the summary of a meeting including key points, decisions, and action items.' It specifies the verb ('Get') and resource ('summary of a meeting') with details on content (key points, decisions, action items). However, it doesn't explicitly differentiate from sibling tools like 'get_transcript' or 'find_action_items', which is why it doesn't achieve a perfect score.
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 provides implied usage guidance: it mentions generating automatically if not yet available, suggesting it's for retrieving or creating summaries. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_transcript' for raw content or 'find_action_items' for specific extraction, and doesn't specify prerequisites or exclusions.
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?
No annotations are provided, so the description carries full burden. It describes output content but doesn't disclose behavioral traits such as authentication needs, rate limits, data sources, or potential side effects (e.g., if it triggers notifications or modifies data). For a read operation with zero annotation coverage, this is a significant gap in transparency.
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 front-loaded with the core purpose in the first sentence, followed by specific content details in a concise list. Every sentence earns its place by clarifying scope and output, with no redundant or vague language, making it highly efficient and well-structured.
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 moderate complexity (consolidated analytics), no annotations, and no output schema, the description is partially complete. It covers purpose and output content adequately but lacks details on behavioral aspects and return format, leaving gaps that could hinder an agent's effective use without further context.
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%, with the parameter 'days' fully documented in the schema (number, range 1-90, default 7). The description adds no additional parameter semantics beyond implying a time period, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for gaps.
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: 'Get a consolidated digest of all your meetings over a time period' with specific content details (total meeting time, decisions, action items, per-meeting summaries). It distinguishes from siblings like 'get_summary' (singular) or 'list_meetings' (raw listing) by emphasizing consolidation and comprehensive analytics. However, it doesn't explicitly name alternatives, keeping it at 4 rather than 5.
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 context ('over a time period') and content scope, suggesting it's for retrospective analysis rather than real-time or future-focused tasks. However, it lacks explicit guidance on when to use this versus alternatives like 'find_action_items' (specific extraction) or 'get_summary' (single meeting), and doesn't mention prerequisites or exclusions, leaving usage somewhat inferred.
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?
No annotations are provided, so the description carries the full burden. It states the tool retrieves account info, implying a read-only operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, error conditions, or response format. This leaves gaps in understanding how the tool behaves beyond its basic purpose.
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 front-loads the purpose and specifies the retrieved information without any wasted words. It's appropriately sized for a simple tool with no parameters.
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 output schema, no annotations), the description is adequate for understanding what it does but incomplete for behavioral context. It covers the purpose and data retrieved but lacks details on authentication, response structure, or error handling, which are relevant for a tool that might involve account-sensitive information.
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 doesn't add parameter semantics, but this is acceptable given the lack of parameters, aligning with the baseline score for zero parameters.
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 ('Get') and resource ('Convo account info'), specifying what information is retrieved ('subscription tier and API usage stats'). However, it doesn't explicitly differentiate from sibling tools, which are all meeting-related, so this distinction is implied rather than stated.
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 context through 'your Convo account info,' suggesting it's for retrieving personal account details, but provides no explicit guidance on when to use this versus alternatives or any prerequisites. Sibling tools are meeting-focused, so this tool's distinct purpose is clear by contrast, but not explicitly stated.
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. While it mentions what information is returned (owner, priority, meeting source), it doesn't address important behavioral aspects like whether this is a read-only operation, if there are rate limits, authentication requirements, or how results are structured/paginated. The description provides basic output format but lacks operational 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?
Two concise sentences that efficiently convey purpose and output format. The first sentence states the core function, the second specifies what information is returned. No wasted words or redundant information. Perfectly front-loaded with the essential information.
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?
For a tool with 2 parameters, 100% schema coverage, and no output schema, the description provides adequate but minimal context. It covers the purpose and output format but lacks behavioral details that would be important for an AI agent (like whether this requires specific permissions, how results are structured, or operational constraints). The description is complete enough for basic understanding but has clear gaps.
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 schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions temporal scope ('recent meetings') which aligns with the 'days' parameter but doesn't provide additional semantic context. Baseline 3 is appropriate when schema does the heavy lifting.
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 ('find all action items'), resource ('across your recent meetings'), and scope ('shows who owns each item, priority, and which meeting it came from'). It distinguishes itself from siblings like 'get_summary' or 'list_meetings' by focusing specifically on action items rather than general meeting information.
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 context ('across your recent meetings') but doesn't explicitly state when to use this tool versus alternatives like 'get_summary' or 'list_meetings'. No explicit guidance is provided about when-not-to-use or prerequisites, though the mention of 'recent meetings' suggests temporal limitations.
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 of behavioral disclosure. It adds some context: it describes the feedback generation behavior ('Generates automatically if not yet available'), which is useful beyond basic function. However, it lacks details on permissions, rate limits, error conditions, or response format. For a tool with no annotations, 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 appropriately sized and front-loaded: the first sentence clearly states the purpose and outputs, and the second sentence adds critical behavioral context. Every sentence earns its place with no wasted words, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (retrieving/generating coaching feedback), no annotations, and no output schema, the description is partially complete. It covers the core function and auto-generation behavior but lacks details on output structure, error handling, or integration with sibling tools. This is adequate for basic use but leaves gaps for robust agent operation.
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%, with the meeting_id parameter fully documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides (e.g., format examples or constraints). With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.
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: 'Get AI coaching feedback for a meeting' with specific outputs listed (communication score, strengths, growth areas, talk-to-listen ratio). It distinguishes from siblings like get_summary or get_transcript by focusing on coaching feedback rather than general summaries or raw transcripts. However, it doesn't explicitly differentiate from all possible alternatives (e.g., ask_about_meeting might also provide feedback).
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 provides implied usage guidance: it's for retrieving AI coaching feedback for meetings, and it mentions that feedback 'Generates automatically if not yet available,' suggesting it can be used both to retrieve existing feedback and trigger generation. However, it doesn't explicitly state when to use this tool versus alternatives like ask_about_meeting or get_summary, nor does it provide exclusions or prerequisites.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's actions (searching, pulling, consolidating) but lacks details on behavioral traits such as permissions required, rate limits, whether it modifies data, response format, or error handling. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.
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, starting with the main purpose ('Prepare a briefing for an upcoming meeting') and then detailing the process in a single, efficient sentence. Every sentence earns its place by explaining the tool's functionality without unnecessary words.
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 (involving searching and consolidating data from past meetings), no annotations, and no output schema, the description is incomplete. It explains what the tool does but lacks details on the output format, error conditions, or dependencies. However, it adequately covers the purpose and basic usage, making it minimally viable but with clear gaps.
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 schema description coverage is 100%, so the schema already documents both parameters ('search' and 'max_past_meetings') with descriptions. The description adds some context by mentioning 'person name, company name, or topic' for the search parameter, but this is largely redundant with the schema. It does not provide additional meaning beyond what the schema offers, meeting the baseline for high 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 tool's purpose with specific verbs ('prepare a briefing', 'searches past meetings', 'pulls summaries and open action items', 'returns a consolidated briefing') and distinguishes it from siblings by focusing on preparation for upcoming meetings rather than retrieval, analysis, or sharing of meeting data. It explicitly mentions the resource ('meetings') and the outcome ('show up prepared').
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 ('for an upcoming meeting' and 'to show up prepared'), implying it's for preparation purposes. However, it does not explicitly state when not to use it or name alternatives among the sibling tools (e.g., 'get_summary' for summaries or 'find_action_items' for action items), which would be needed for a score of 5.
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:

[![mcp-server MCP server](https://glama.ai/mcp/servers/itsconvo/mcp-server/badges/card.svg)](https://glama.ai/mcp/servers/itsconvo/mcp-server)

Score Badge

Copy to your README.md:

[![mcp-server MCP server](https://glama.ai/mcp/servers/itsconvo/mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/itsconvo/mcp-server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/itsconvo/mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server