CNC catalog MCP for TWAIT factory: search machines, specs, images, leads.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 3.1/5 across 10 of 10 tools scored. Lowest: 2.4/5.
Each tool has a distinct purpose, from searching machines to submitting leads and subscribing to events. No overlapping functionality.
All tools follow a consistent verb_noun snake_case pattern (e.g., list_categories, get_machine_detail). The naming is uniform and predictable.
10 tools is well-scoped for a CNC machine catalog, covering search, details, pricing, inquiries, orders, and events without being excessive.
The tool set covers the full user-facing workflow: discovery (search, categories, details, images), pricing, ordering (birzha), inquiry (ask_manager, submit_lead), and event subscriptions. No obvious gaps.
ask_managerCInspectЗадать вопрос живому менеджеру (нужен API-ключ)
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| No | |||
| phone | No | ||
| api_key | No | ||
| question | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states that the tool asks a question and requires an API key. It does not describe the behavior of the tool (e.g., response time, whether it's synchronous, what happens after submission), leaving significant gaps.
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 is front-loaded with the main purpose. However, it is too brief and lacks necessary detail, which slightly reduces its effectiveness.
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 tool has 5 parameters, no output schema, and no annotations, the description is very incomplete. It does not explain return values, prerequisites beyond the API key, or how the question is processed, leaving the agent with insufficient context.
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 by explaining parameters. The description only mentions the API key requirement, but does not explain the purpose of name, email, phone, or question. The names are self-explanatory, but additional context is missing.
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 ('ask a question') and the resource ('live manager'), and adds the requirement for an API key. However, it does not distinguish this tool from its siblings, which are all machine-related, but an explicit differentiation would improve clarity.
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 only mentions the need for an API key but provides no guidance on when to use this tool versus alternatives. There is no mention of when not to use it or what scenarios are appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_machine_priceAInspectОнлайн-конфигуратор станков Каменского завода. Расчёт ориентировочной стоимости с учётом шпинделя и вакуумного стола.
| Name | Required | Description | Default |
|---|---|---|---|
| model | Yes | Модель или product_number станка | |
| vacuum_table | No | Наличие вакуумного стола | |
| spindle_power | No | Мощность шпинделя (2.2kW, 3.2kW, 4.5kW, 6kW) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral disclosure burden. It adds context beyond the input schema by indicating the tool is an 'online configurator' that calculates 'approximate cost', suggesting a non-destructive, estimated result. However, it does not detail potential errors, rate limits, or authentication needs.
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 conveys the essential purpose without any wasted words. It is well-suited for quick comprehension, though it could be more structured by front-loading the action.
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 three parameters, no output schema, and no annotations, the description adequately explains the tool's purpose and relevant parameters. It could be improved by noting the return value format (e.g., price range), but it is sufficient for a simple calculator tool.
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 100%, so the baseline is 3. The description mentions 'spindle and vacuum table' options, which correspond to the parameters, but does not add significant new meaning beyond the schema descriptions. It reinforces the context of the calculation but does not clarify parameter constraints or format.
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 purpose: it is an online configurator for Kamensky plant machines, calculating approximate cost with spindle and vacuum table options. This provides a specific verb-resource relationship and distinguishes it from sibling tools like 'search_machines' or 'get_machine_detail'.
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 usage for obtaining a price estimate but does not explicitly state when to use this tool versus alternatives, nor does it provide when-not-to-use guidance or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_birzha_ordersAInspectСписок активных заказов на фрезеровку и раскрой с Биржи Заказов Завода для выбранного региона/города.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | Город для поиска заказов | |
| limit | No | default 10, max 30 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states 'list of active orders', implying a read operation, but does not disclose authentication needs, side effects, rate limits, or response format.
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 only 12 words, immediately stating the purpose and scope. No wasted words.
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 there is no output schema and only 2 parameters, the description is adequate but not complete. It does not clarify pagination beyond the limit parameter, nor does it explain the order object structure or the meaning of 'region' vs 'city' (only city parameter exists).
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 100%, with descriptions for both 'city' and 'limit' parameters. The description adds minimal extra meaning beyond the schema, simply reiterating the geographic filter. Baseline 3 is appropriate.
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 explicitly states the tool lists active orders for milling and cutting from the Factory Orders Exchange, and specifies it is filtered by region/city. This clearly distinguishes it from sibling tools like search_machines or get_company_info.
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 should be used when you need active orders for a selected region/city, but it does not explicitly state when to use it versus alternatives, nor does it mention prerequisites or 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.
get_company_infoBInspectКонтекст компании: контакты, сайты, llms/MCP discovery URLs
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It discloses that the tool returns contacts, websites, and URLs, but does not mention any behavioral traits such as authentication requirements, data freshness, or potential side effects. This is a significant gap for an information retrieval 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?
The description is a single, front-loaded sentence that communicates the tool's purpose efficiently. Every word adds value, with no redundant or unnecessary text.
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 description lists the types of information returned (contacts, sites, URLs), but without an output schema, more detail about the response structure would be helpful. It is minimally adequate but lacks completeness regarding format or further context.
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 input schema has zero parameters, so schema coverage is 100%. Per guidelines, baseline is 3 even without parameter info in the description. The description adds no parameter semantics because there are none to describe.
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 specifies the tool returns company context including contacts, websites, and discovery URLs. It uses a specific verb ('get') and resource ('company info'), and the listed content distinguishes it from sibling tools focused on machines, orders, and other domains.
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 provided on when to use this tool versus alternatives. There is no mention of prerequisites, contexts, or when not to use it, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_machine_detailCInspectПолная карточка станка по product_number (id)
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | product_number станка |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose read-only nature, permissions, or any side effects. For a retrieval tool, 'full card' hints at read operation, but explicit behavior is missing.
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?
Very short phrase, but it conveys the purpose. Could be a proper sentence. Adequate but not optimized for quick scanning.
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?
No output schema, and the description does not specify the return format or any nuances. For a one-parameter tool, more details on what 'full card' contains would improve completeness.
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 100%; the description adds minor clarification that 'id' is the product number. Baseline 3 is appropriate as the description adds little beyond the schema.
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 returns the full machine card by product number, using a specific verb ('get' implied) and resource. It distinguishes from sibling tools like search_machines, though not explicitly.
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 or alternatives. The description implies use when a product number is available, but offers no exclusions or context for when to prefer other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_machine_imagesCInspectИзображения станка в высоком разрешении
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only mentions 'high resolution' but fails to disclose image count, format, size limits, or authorization 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?
The description is very short (3 words), which is concise but under-specified. It could include more detail without losing conciseness.
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 tool with one parameter and no output schema, the description still lacks context on return value structure, image count, or typical usage scenarios, which is insufficient.
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?
Only parameter 'id' is described in schema but not in description. Since schema coverage is 0%, the description should explain what id represents (e.g., machine ID) but does not.
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 that the tool retrieves high-resolution images of a machine, which is a specific resource distinct from siblings like get_machine_detail that returns details.
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 (e.g., get_machine_detail for non-image data) or any context on prerequisites like whether the machine ID must exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesAInspectСписок категорий станков с количеством
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations and the description does not disclose behavioral traits such as data source, permissions, or refresh rate. Only the basic function is stated.
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 gets to the point. It is not wasteful, though it is minimal.
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 tool with no parameters, no output schema, and no annotations, the description is adequate but minimal. It indicates quantity is included, but could elaborate on return format.
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?
There are zero parameters, so parameter description is not needed. Baseline 4 applies as no compensation is required.
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 lists machine categories with quantity, using a specific verb and resource. It distinguishes from siblings like search_machines and get_machine_detail.
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 explicit guidance on when to use this tool versus alternatives. Usage is implied (e.g., before searching machines), but no exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_machinesBInspectПоиск ЧПУ станков по типу (фрезерный, лазерный, плазменный), габаритам поля и обрабатываемому материалу.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Свободный поисковый запрос | |
| type | No | ||
| limit | No | 1-50, default 10 | |
| category | No | ||
| material | No | МДФ, фанера, алюминий, сталь, камень | |
| max_price | No | ||
| min_price | No | ||
| working_area | No | Например: 1325, 1530, 2030, 6090 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only lists filtering criteria but does not disclose behavioral traits such as read-only nature, pagination, sorting, or response format. Essential context for a search tool is missing.
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 sentence that front-loads the core purpose. Every word earns its place, with no redundancy or filler. It is maximally concise.
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 8 optional parameters and no output schema, the description only explains 3 parameters. It omits details on combining filters, default behavior, result ordering, or output format. For a search tool of this complexity, the description is incomplete.
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 50%. The description adds meaning for three parameters (type, working_area, material) by explaining their roles and providing examples. However, it does not cover the other five parameters (q, limit, category, max_price, min_price), thus adding partial value.
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 searches CNC machines by type, field dimensions, and material. The verb 'Поиск' and resource 'ЧПУ станков' are specific. It effectively distinguishes itself from sibling tools like get_machine_detail or get_machine_images, which are not search tools.
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 usage for filtering by type, dimensions, and material, but does not explicitly state when to use this tool versus alternatives (e.g., other search or detail tools). No prerequisites or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_leadCInspectОтправить заявку менеджеру (нужен API-ключ)
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| No | |||
| phone | No | ||
| api_key | No | ||
| comment | No | ||
| machine_id | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states an API key is needed, implying authentication, but does not reveal whether the operation is destructive, reversible, or what side effects occur (e.g., does it create a record, send a notification?). No mention of rate limits, data retention, or confirmation.
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 short sentence, making it very concise. However, it sacrifices clarity and completeness for brevity. It is front-loaded with the action and requirement, but does not expand on essential details. Nonetheless, every word is informative.
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 complexity (6 parameters, no schema descriptions, no output schema, no annotations), the description is grossly incomplete. It fails to explain what a 'lead' is, how the parameters are used, what the return value is, or any important behavioral details. The tool cannot be reliably invoked without external knowledge.
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 adds no meaning to any of the 6 parameters. It only mentions 'api_key' in the main description without explaining its role or how it should be provided. The parameters 'name', 'email', 'phone', 'comment', and 'machine_id' are left entirely unexplained.
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 (submit a lead to a manager) and a key requirement (API key). However, it could be more specific about what constitutes a 'lead' and how it relates to the tool name. It is distinguishable from sibling tools like ask_manager or calculate_machine_price.
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 no guidance on when to use this tool versus alternatives. It only mentions the need for an API key, but does not explain scenarios, prerequisites, or exclusions. Sibling tools like ask_manager suggest alternative ways to interact with managers, but no differentiation is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
subscribe_to_factory_eventsBInspectПодписать ИИ-агента на webhook-уведомления об изменении цен, новых заказах Биржи или складских обновлениях.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | Идентификатор агента | |
| event_types | Yes | ||
| webhook_url | Yes | HTTPS URL для POST webhooks |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavioral traits, but it only states the core function. It does not mention side effects (e.g., whether subscribing triggers immediate notifications), persistence, auth requirements, rate limits, or cancellation mechanisms.
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 sentence that efficiently conveys the tool's purpose, event categories, and target. No extraneous information is included, making it easy to parse quickly.
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 subscription tool with no output schema, the description omits critical details like what the response looks like (e.g., confirmation ID), error handling, or how to verify subscription success. While the purpose is clear, important operational context is missing.
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 67% (agent_id and webhook_url have descriptions, but event_types does not). The description adds no additional parameter meaning beyond the schema, such as explaining the significance of each event type or providing usage examples.
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 ('подписать' / subscribe), the target resource ('ИИ-агента' / AI agent), and the specific notification types (price changes, Exchange orders, warehouse updates). It distinguishes this tool from siblings, none of which involve webhook subscriptions.
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 provided on when to use this tool versus the siblings or under what conditions it is appropriate. There are no prerequisites, exclusions, or alternative tools mentioned, leaving the agent to infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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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
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