cursor-yougpu-mcp

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct resource or action: balance, GPU catalog, offers, SSH keys, and instance lifecycle operations. There is no ambiguity between list_instances and get_instance, or between list_gpus and list_offers, as they operate on different levels of detail.
Naming Consistency4/5
Names follow a consistent yougpu_verb_noun pattern for most tools (list, get, create, stop, start, delete). The only deviation is 'yougpu_balance', which is a noun rather than verb-first, but it is still predictable and readable.
Tool Count5/5
With 11 tools, the server is well-scoped for managing GPU instances. It includes essential operations for wallet, catalog, offers, SSH keys, and full instance lifecycle without unnecessary bloat.
Completeness5/5
The toolset covers the complete workflow: checking balance, browsing GPUs/offers, managing SSH keys, creating instances, monitoring readiness, and performing lifecycle operations (start, stop, delete). There are no critical gaps for the stated purpose.
Average 3.8/5 across 11 of 11 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
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.
Add a glama.json file to provide metadata about your server.
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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, and the description only says 'Start a previously stopped instance' without disclosing side effects, errors, idempotency, or what happens if the instance is already running. It fails to inform the agent about the tool's behavioral consequences beyond the basic action.
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, focused sentence with no redundant information. It is front-loaded and efficiently communicates the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description lacks crucial context about return values, asynchronous behavior, or failure modes. The sibling tool yougpu_wait_ready implies starting may be asynchronous, but the description does not mention this, making it insufficient for an agent to fully rely on.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the instance_id parameter beyond what the schema already shows. No semantic meaning is added to aid the agent in understanding how to use the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action with a specific verb 'Start' and resource 'previously stopped instance', distinguishing it from sibling tools like stop, create, and delete. It unambiguously conveys what the tool does.
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?
No guidance is provided on when to use this tool, prerequisites (e.g., the instance must be stopped), or alternatives. The existence of sibling tools like yougpu_wait_ready suggests a follow-up action, but the description gives no context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It usefully reveals that the list includes both active and terminated history, which is a non-obvious behavioral detail. However, it does not mention pagination behavior, response format, or any implicit constraints beyond the scope. The read-only nature is implied by 'List' but not explicitly stated, leaving some 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 a single sentence of eight words, front-loaded with the verb and resource. Every word contributes meaning, with no redundant or filler content. It is appropriately concise.
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 and no output schema, the description should provide enough context to use the tool correctly. It clarifies the result scope but omits essential operational details like pagination (page/limit), default limits, and what fields each instance includes. This is insufficient for a no-annotation tool with two undocumented parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions for the two parameters page and limit (0% coverage). The description does not reference these parameters at all, failing to compensate for the missing schema descriptions. It only explains the result scope, not how to control pagination or limits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action and resource: 'List YouGPU instances'. The parenthetical '(active and terminated history)' specifies the scope, distinguishing this tool from siblings like yougpu_list_gpus (GPU catalog) and yougpu_list_offers (offers). This is a specific, unambiguous purpose.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of scenarios, exclusions, or related tools such as yougpu_get_instance for single-instance details or yougpu_create_instance for provisioning. The description only states what the tool does, not when to use it.
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 exist, so the description carries the transparency burden. It adds useful behavioral details (keeps disk, may reserve storage cost), but it does not disclose other relevant traits such as the instance being resumable via start_instance or what happens to compute billing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with a parenthetical caveat. Every word serves a purpose, making it both concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema), and the description covers the core function and the key distinction from delete. However, it omits an explicit note about reversibility (start_instance) and does not clarify the instance_id source, which would make it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the instance_id parameter at all. While the parameter name is self-explanatory within context, the rule requires the description to compensate for low coverage; it fails to do so, leaving the user to infer how to identify the instance.
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 starts with a specific verb ('Stop') and resource ('a running instance'), clearly stating the tool's function. The parenthetical 'keeps disk' distinguishes this from sibling delete_instance, so it differentiates well from related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by noting it keeps disk and may reserve storage cost, contrasting with delete. However, it does not explicitly state when to use this over alternatives like start_instance or delete_instance, nor does it mention prerequisites (e.g., instance must exist and be running).
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. It discloses the config fallback for ssh_key_ids and the dependency on offers data, which is useful. However, it doesn't disclose side effects, permission requirements, or lifecycle behavior (e.g., whether the instance starts immediately, if it is created in a stopped state).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the primary purpose front-loaded and every clause earning its place. It efficiently conveys the core action, prerequisites, and a parameter default.
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?
This is a create tool with 6 parameters, no output schema, and no annotations. The description provides a few hints but leaves two parameters undocumented and gives no indication of return values, errors, or post-creation steps (e.g., wait_ready). A more complete description would explain template_id and storage_drive_id and what the response contains.
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 only 33% (image_id and instance_name). The description adds meaning for offer_id (must come from offers) and ssh_key_ids (default to config if omitted), but leaves template_id and storage_drive_id completely unexplained. It partially compensates for the low schema coverage but not fully.
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 opens with 'Create a GPU instance,' which is a specific verb+resource pair that clearly identifies the tool's function. It also adds that offer_id and image_id come from offers, further distinguishing this creation tool from the list/get/stop/start/delete siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states that offer_id and image_id are required and sourced from offers, implying the need to call list_offers first. It also gives clear guidance that ssh_key_ids can be omitted and will default to YOUGPU_SSH_KEY_IDS from config, which is a useful usage pattern. It doesn't explicitly mention alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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. It discloses that the tool returns a summary and raw payload, which is useful. However, it does not explicitly state that the operation is read-only, nor does it mention error behavior or authentication requirements.
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, direct sentence that conveys the purpose and return format with no unnecessary words. It is concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-by-id tool with one parameter and no output schema, the description sufficiently indicates the operation and return format. It does not explain the meaning of 'summary' versus 'raw payload', but this is a minor gap given the low complexity.
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 description references 'by id' and thus identifies instance_id as the identifier parameter. However, it adds minimal detail beyond the schema: it does not explain what an instance ID is, where to find it, or provide examples. With 0% schema description coverage, the description only partially compensates.
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 verb 'Get', the resource 'one instance by id', and the output format ('summary + raw payload'). It is distinct from the sibling tool yougpu_list_instances which retrieves multiple instances.
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 when needing a single instance by ID, but it does not explicitly mention alternatives or when not to use it. For example, it does not state that yougpu_list_instances should be used for listing all instances.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It discloses key behavioral traits: polling continues until ACTIVE/INSTALLING with IP or ERROR, and there is a default timeout of 10 minutes. However, it does not mention what happens on timeout (error vs. return), nor does it specify if the operation is read-only, which would be useful but not critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core behavior and default timeout without unnecessary words. Every element earns its place, making it highly concise 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 that there is no output schema and no annotations, the description should explain more about return values and edge cases. It mentions 'with IP' but does not detail the full return structure or what occurs on timeout. For a simple polling tool, it provides the essential behavior, but gaps remain in error handling and return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameters, but it only mentions 'Default timeout 10 minutes' without naming timeout_ms or explaining its range. It does not describe poll_interval_ms at all, and instance_id is only implied by 'Poll instance'. This leaves parameter semantics largely unexplained.
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 uses the specific verb 'poll' with the resource 'instance' and clearly states the intended outcome: wait until ACTIVE/INSTALLING with IP or ERROR. This distinguishes it from siblings like get_instance (single fetch) and list_instances (listing), so purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after instance creation ('Poll instance until...') but does not explicitly state when to use it versus alternatives like get_instance. No when-not-to-use or alternative references are provided, so guidance is only implicitly inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool lists models with price ranges and stock, indicating a read-only operation, but it does not explicitly mention side effects, authentication requirements, or any pagination/live data behavior. The description is minimal but not misleading.
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, concise sentence that conveys all necessary information without redundancy. Every part of the sentence adds value: the action, the object, and the content details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zero-parameter tool with no output schema, the description adequately covers the purpose and what data is returned (price ranges and stock). It could mention whether results are paginated or sorted, but these are not critical for a catalog list. Overall, it is sufficiently complete for this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema already provides complete coverage (100%). The description does not need to explain parameters, and the baseline of 4 is appropriate since there is no parameter complexity to address.
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 uses a specific verb 'List' and identifies the resource 'GPU models' within the 'YouGPU catalog', adding details about price ranges and stock. This clearly distinguishes it from sibling tools like list_offers and list_instances, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (to see available GPU models and pricing) but provides no explicit context for when to use this tool versus alternatives. It does not mention exclusions or scenarios where another list tool would be more appropriate, so guidance is only implicit.
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 burden. 'List' indicates a read-only operation, but no additional behavioral details are given (e.g., authentication requirements, pagination, or return format). For a simple list tool this is minimally adequate.
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 concise sentence that front-loads the action and resource. No superfluous information is included.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema), the description is functional. However, it does not explicitly state what the returned list contains (e.g., key names, IDs), which would be useful but is not strictly necessary for such a simple list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema coverage is 100% (vacuously). The description correctly does not reference parameters, and the baseline for 0-parameter tools is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (List) and the resource (SSH keys registered in the YouGPU account), making it specific and distinct from sibling tools like list_gpus or list_instances.
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 when you need to see SSH keys, but does not provide explicit when-to-use guidance or name alternatives. The account scope is clear, but no exclusions or alternative tool suggestions are offered.
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. The verb "Get" implies a safe read operation, and the listed fields make the return content clear. However, it does not mention authentication requirements, error behavior, or that no parameters are needed (though that is self-evident). This is adequate but minimal.
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?
A single, concise sentence that starts with an action verb and lists the key output fields. No wasted words, and the parenthetical enumeration is efficiently packed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, no-parameter read tool, the description is fully self-contained. It specifies the resource and the exact fields returned, so an agent knows what to expect. No output schema exists, so the description compensates by stating the return fields.
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, so the schema coverage is trivially 100%. There is nothing to explain about parameters, and the description adds meaning by indicating what the returned balance fields represent. The baseline for 0-param tools is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: "Get YouGPU wallet balance". It also enumerates the returned data fields (available, reserved, hourly_rate, total), unambiguously distinguishing it from sibling tools that deal with GPUs, instances, and SSH keys.
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 tool's purpose is obvious, but the description does not explicitly state when to use it or contrast it with alternatives. There are no alternatives mentioned, and no contextual guidance like "before creating an instance, check your balance". The usage is implied but not explicitly spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It accurately states that the action is permanent and stops GPU billing, adding important context beyond the tool name. It does not mention other potential effects (e.g., resource cleanup) but covers the most critical destructive aspect.
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, information-dense sentence. It includes the action, permanence, billing impact, and even the underlying HTTP endpoint, all without redundancy. Every word contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter destructive tool, the description covers the essential behavioral aspects: permanent deletion and billing stop. It lacks an explicit note about irreversibility (though 'permanently' implies it) and return value, but these are minor gaps. The tool's simplicity and the endpoint reference make this adequate.
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 sole parameter instance_id has no description in schema, and the tool description does not explicitly define it. However, given the tool name 'delete_instance' and the parameter name, its meaning is self-evident. The description adds no new semantic detail, but the parameter is trivially clear, making this adequate.
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 specifies a distinct action: terminate/delete instance permanently and stop GPU billing. This clearly differentiates it from sibling tools like stop_instance and start_instance, which suggest temporary state changes, making the tool's role unambiguous.
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 implies when to use this tool by emphasizing permanence and billing implications, contrasting with stop/start. While it doesn't explicitly name an alternative or say 'use this instead of stop when...', the context is clear enough for an agent to infer that this is for permanent termination rather than temporary pausing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
As a list operation, the description implies read-only behavior and discloses the expected response fields (offer_id, price/hour, region, images). It adds the 'in-stock' filter, which clarifies the scope. Given no annotations, this is adequate but could mention safety or side effects explicitly.
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 without filler. First sentence states the action and prerequisite; second lists the return fields efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 1-parameter list tool, the description covers purpose, prerequisite, and return fields. It doesn't mention pagination or auth, but these are not critical for a basic list; the reference to yougpu_list_gpus completes the workflow context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents gpu_id with 100% coverage, so the baseline is 3. The description additionally references yougpu_list_gpus as the source, reinforcing the parameter's origin and adding practical usage context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with the resource 'in-stock offers for a GPU model id', making it clear this tool fetches offers rather than GPU models. It also references yougpu_list_gpus as the source for the id, distinguishing it from sibling list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly guides usage by noting the id comes from yougpu_list_gpus, indicating a prerequisite call. It clarifies this tool is for offers, not for GPU models or instances, but does not explicitly state when not to use it or name alternative tools.
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:

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

Score Badge

Copy to your README.md:

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

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/eldarknz/cursor-yougpu-mcp'

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