Voice School Lesson Booking
Server Details
Request online singing lessons with Voice School and Daria Klishina.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Tool Definition Quality
Average 3.3/5 across 9 of 9 tools scored. Lowest: 2.7/5.
The lesson tools are cleanly separated: request creation, options listing, availability search, and general info all target different resources/actions. The main confusion risk is in the social pipeline, where create_social_post and publish_social_post can both look like the way to get a post live, and the two upsert tools are behaviorally similar even though their targets differ.
Most names follow a snake_case verb_noun pattern: create_lesson_request, list_social_posts, publish_social_post, search_lesson_availability, upsert_social_channel. However, voice_school_info breaks the verb pattern, and create_social_post is actually a create-or-update operation while other create/update tools use the upsert prefix, creating a minor semantic inconsistency.
At nine tools the absolute count is reasonable and within the ideal 3-15 range. However, five of the nine tools target social media management, which feels like a second domain bolted onto a lesson-booking server, so the set is slightly overbroad for its stated purpose.
The lesson-request flow covers info, options, availability, and request creation, but then stops; there is no way to list, update, or cancel requests, though creation is intentionally request-first. The social-post flow supports create/update, publish, and list, but only lists published posts and has no delete/unpublish or draft-listing operation, leaving lifecycle coverage incomplete.
Available Tools
9 toolscreate_lesson_requestAInspect
Create a request-first lead for an online vocal lesson. Requires name and at least one contact method. This never confirms a lesson or creates a private schedule item.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| No | |||
| phone | No | ||
| message | No | ||
| language | No | en | |
| telegram | No | ||
| No | |||
| coach_slug | No | daria-klishina | |
| city_context | No | ||
| service_slug | No | ||
| source_agent | No | ||
| requested_start | No | ||
| requester_timezone | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It explains the creation of a lead, the requirement of at least one contact method, and explicitly limits its scope by stating it cannot confirm lessons or create schedule items. This is meaningful context that goes beyond the basic schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the primary purpose. The second sentence adds a requirement and an exclusion, both earning their place without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 13 parameters and an output schema, the description provides essential context about the tool's purpose and constraints. It does not explain return values (covered by output schema) or every parameter, but it offers enough for an agent to understand the action and its limitations. Sibling tool differentiation could be stronger, but the description is self-sufficient for most cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds the key constraint that 'requires name and at least one contact method,' which clarifies the relationship between the name and contact fields. However, it does not describe the other 12 parameters, relying on the schema's titles and defaults, so it only partially compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Create a request-first lead for an online vocal lesson.' It distinguishes this from siblings by explicitly noting it never confirms a lesson or creates a schedule item, which sets it apart from tools like search_lesson_availability or list_lesson_options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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: when you need to initiate a request-first lead. It also includes an explicit exclusion ('never confirms a lesson or creates a private schedule item'), which helps avoid misuse. However, it does not directly name alternative tools or provide explicit when-not-to-use guidance beyond this exclusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_social_post_draftCInspect
Create or update a trainer social post with SEO title, description, keywords, tags, original source URL and ordered text/video blocks. Requires SOCIAL_POSTS_MCP_WRITE_TOKEN as write_token.
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | ||
| slug | No | ||
| tags | No | ||
| title | No | ||
| blocks | No | ||
| excerpt | No | ||
| publish | No | ||
| keywords | No | ||
| raw_text | No | ||
| seo_title | No | ||
| coach_slug | Yes | ||
| channel_url | Yes | ||
| write_token | Yes | ||
| channel_slug | Yes | ||
| channel_title | Yes | ||
| language_code | No | ru | |
| source_platform | No | TELEGRAM | |
| source_post_url | Yes | ||
| external_post_id | No | ||
| meta_description | No | ||
| source_published_at | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full disclosure burden. It usefully discloses the token requirement and the dual create/update semantics, but it does not mention that the publish parameter can take a draft live, nor how an update overwrites existing content — both consequential behaviors for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each earning its place: the first summarizes purpose and content shape, and the second states the authentication requirement. It is dense but not bloated, and the purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 21-parameter creation tool with zero annotations and zero schema descriptions, this description is incomplete. The update-vs-create trigger, the redundancy of channel_title/channel_url alongside channel_slug, and the publish flag's side effects are all left to inference. The output schema mitigates only return-value questions, not invocation semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it names only the headline content fields (SEO title, keywords, tags, source URL, text/video blocks). The six required parameters (coach_slug, channel_slug, channel_title, channel_url, source_post_url, write_token) and the remaining optional fields such as slug, excerpt, language_code, and source_platform are left unexplained in both schema and description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb+resource ('Create or update a trainer social post') and enumerates the content payload (SEO title, description, keywords, tags, source URL, ordered text/video blocks). The name 'draft' plus the sibling publish_social_post imply a drafting stage, but the description does not explicitly differentiate itself from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 siblings such as publish_social_post, upsert_social_channel, or list_social_posts. The only prerequisite mentioned is the write token, so an agent gets no selection cues and no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_lesson_optionsAInspect
List active lesson services and prices for a coach from the live Voice School database.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | en | |
| coach_slug | No | daria-klishina |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
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 does not state that the tool is read-only or describe side effects, but the verb 'List' implies a safe read operation. Details like 'active' and 'live database' add some behavioral context, but return format and any caveats are not disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the tool's purpose without unnecessary words. It earns its place and is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with 2 optional parameters and an output schema that describes return values. The description is adequate for a listing tool but leaves parameter semantics unexplained. Given the output schema, return values need not be described, but parameter guidance would make the description more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 2 parameters (language, coach_slug) with 0% description coverage. The description mentions 'for a coach' which hints at coach_slug, but does not explain language or how these parameters affect the results. The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List'), the resource ('active lesson services and prices for a coach'), and the context ('from the live Voice School database'). This is distinct from sibling tools like create_lesson_request (write) and search_lesson_availability (search availability).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for viewing a coach's offerings, which is clearly different from creating a request or searching availability. However, it does not explicitly state 'use this when...' or mention alternatives, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_social_postsBInspect
List published trainer social posts with canonical and original source URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| language | No | ru | |
| platform | No | ||
| coach_slug | No | ||
| channel_slug | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It communicates a read-only list of published posts and the URL fields returned, but it does not disclose pagination, ordering, scope (e.g., current trainer vs any trainer), or any auth/permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no filler; the key verb, resource, status filter, and return detail are all front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists, so return-shape concerns are reduced, and the description covers the main purpose. However, it is incomplete for a five-parameter tool: an agent cannot tell from the description which optional filters are available or how they behave.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the five undocumented parameters. It does not explain limit, language, platform, coach_slug, or channel_slug, nor their defaults or filtering behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('published trainer social posts') and adds output detail (canonical and original source URLs). This clearly distinguishes it from sibling tools like create_social_post_draft, publish_social_post, or list_lesson_options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied: retrieve published trainer social posts. The word 'published' hints at when it applies, but the description gives no explicit guidance about when to choose this over alternatives or when not to use it, such as when drafts should go to create_social_post_draft.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
publish_social_postAInspect
Publish a prepared trainer social post after source URL validation. Requires SOCIAL_POSTS_MCP_WRITE_TOKEN as write_token.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| write_token | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the disclosure burden and covers meaningful behavioral ground: it requires an auth token and performs source URL validation before publishing. It does not detail side effects such as visibility or irreversibility, but the disclosed auth and sequencing exceed a bare action statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words, and the key action plus required condition are front-loaded. Every sentence adds information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with an output schema, the description is close to sufficient, but the undefined slug and lack of failure behavior/error cases make it only minimally viable for a correct call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain the parameters. It correctly maps write_token to SOCIAL_POSTS_MCP_WRITE_TOKEN, but leaves slug undefined; the agent has to guess what value identifies the prepared post. This is a clear gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Publish') on a specific resource ('prepared trainer social post') and adds a validation step. The word 'prepared' clearly separates it from sibling create_social_post_draft.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this to publish a post that has already been prepared and after source URL validation. It does not explicitly name alternatives or state when not to use the tool, but the context is sufficient to route an agent correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_lesson_availabilityBInspect
Find free requestable lesson times using coach working windows and busy intervals. The response never includes private learner data.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| date_to | No | ||
| date_from | No | ||
| coach_slug | No | daria-klishina | |
| service_slug | No | single-vocal-lesson | |
| user_timezone | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses a key privacy trait ('never includes private learner data') and the calculation basis ('working windows and busy intervals'), but omits authentication, rate-limiting, or failure behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the primary purpose stated first and a secondary privacy note second. Every sentence adds value and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return values are covered, but the tool's core operation and parameter interplay remain underspecified. The description is adequate for a high-level gist but lacks enough context for an agent to confidently invoke it with correct parameters, especially with sibling tools present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description offers no explanation of any parameters, such as coach_slug, date_from/to, or user_timezone. It does not compensate for the missing schema descriptions, leaving parameter semantics entirely to the schema's structural details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: finding free requestable lesson times using coach working windows and busy intervals. It goes beyond a tautology but does not explicitly differentiate from sibling 'list_lesson_options', which may offer similar capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for searching availability but does not provide explicit when-to-use guidance, alternatives, or exclusions. No information distinguishes this from 'list_lesson_options' or indicates when to prefer it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
upsert_social_channelBInspect
Add or update a social channel/group that trainer posts are attached to. Requires SOCIAL_POSTS_MCP_WRITE_TOKEN as write_token.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| slug | Yes | ||
| title | Yes | ||
| platform | Yes | ||
| is_active | No | ||
| coach_slug | Yes | ||
| description | No | ||
| write_token | Yes | ||
| channel_type | No | CHANNEL |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that this is a write operation requiring SOCIAL_POSTS_MCP_WRITE_TOKEN, an important auth prerequisite not covered by annotations (none are provided). However, it does not explain conflict behavior, partial-update semantics, or consequences of changing slug/url, leaving some behavioral burden unmet.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence that names the operation and resource before the auth requirement, with no filler. Every phrase adds signal, and it is appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the schema has no property descriptions and there are no annotations, the description covers only the core action plus one auth parameter. It omits sibling differentiation, required-field rationale, key/conflict semantics, and parameter details, so it is not complete enough for reliable invocation despite the output schema reducing the need to document return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only explains write_token. The meanings and relationships of coach_slug, platform, title, slug, url, is_active, description, and channel_type are left to inference from parameter names, which is insufficient for a nine-parameter upsert.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action ('Add or update') and resource ('social channel/group') and ties it to trainer posts, so an agent knows what entity is being managed. However, it does not explicitly differentiate from the similarly named sibling upsert_trainer_social_link, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; it does not contrast with upsert_trainer_social_link or other sibling tools. The only usage hint is the required write_token, which is a prerequisite rather than a selection rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
upsert_trainer_social_linkCInspect
Add or update a public round social icon link for a Voice School trainer. Requires SOCIAL_POSTS_MCP_WRITE_TOKEN as write_token.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| label | No | ||
| handle | No | ||
| platform | Yes | ||
| is_active | No | ||
| coach_slug | Yes | ||
| write_token | Yes | ||
| display_order | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only reveals that the operation is an upsert and requires a specific token. It does not disclose what happens to an existing link, whether the operation is idempotent, or any side effects beyond add/update.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with the action and resource front-loaded. The odd 'public round' wording is slightly confusing, but otherwise there is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an 8-parameter write tool with no annotations and no parameter descriptions, this definition is incomplete. It omits what 'public round' means, what platform values are valid, and how display_order or is_active affect behavior, leaving an agent to guess from names.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate, but it only explains write_token. The other seven parameters (coach_slug, platform, url, label, handle, is_active, display_order) are left entirely to their names and schema defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Add or update') and a specific resource ('public round social icon link for a Voice School trainer'), which clearly distinguishes it from post-publishing and channel-management siblings. The phrase 'public round' is somewhat ambiguous, but the overall purpose is still evident.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives like upsert_social_channel or create_social_post_draft. The intended use is only implied through the resource name, with no explicit conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
voice_school_infoBInspect
Public description, policy, and catalog links for Voice School online vocal lesson requests.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | en |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It indicates the tool returns informational content but does not clarify whether the operation is read-only, how the language parameter affects output, or what the response contains beyond 'links'. This is minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately states the tool's purpose. There is no redundancy or unnecessary detail, and it is front-loaded with the key terms 'public description', 'policy', and 'catalog links'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a simple info tool with one optional parameter and an output schema (which can explain return values), the description is minimally adequate. However, it omits the role of the 'language' parameter and provides no examples of the links, leaving some ambiguity for an agent deciding between this and sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one optional 'language' parameter with 0% description coverage. The description does not mention this parameter at all, providing no additional meaning beyond the schema. It fails to explain what language affects (likely the language of the returned policy/catalog links) or any constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies what the tool does: it provides public description, policy, and catalog links for Voice School online vocal lesson requests. This is distinct from the sibling tools (create, list, search), though it lacks an explicit verb like 'returns' or 'provides'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: this tool should be used when general information about Voice School is needed, as opposed to creating requests, listing options, or searching availability. However, there is no explicit guidance on when to use it versus alternatives, nor any mention of when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
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Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
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Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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