jungle-grid-mcp-server

Official

by Jungle-Grid

Overview Schema Related Servers Score Discussions(1)

TypeScript

Remote

Server Quality Checklist

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Latest release: v0.1.9
Disambiguation5/5
Each tool targets a distinct operation (submit, cancel, estimate, get status, get logs, list, get artifact, list artifacts) with no overlap. The separation between job management and artifact management is clear.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case (e.g., cancel_job, get_artifact, list_jobs). The naming is predictable and easy to understand.
Tool Count5/5
With 8 tools, the server provides a focused but complete set for managing Jungle Grid jobs. Each tool serves a necessary function without bloat or undersupply.
Completeness4/5
Covers the core job lifecycle (submit, get, list, cancel, estimate, logs, artifacts). Missing an update/retry tool for modifying job parameters, but the core workflow is well-supported.
Average 3.6/5 across 8 of 8 tools scored. Lowest: 3/5.
See the Tool Scores section below for per-tool breakdowns.
- 7 of 14 community issues answered or closed in the last 6 months
- 17 commits in the last 12 weeks
- Last stable release on August 11, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as read-only and non-destructive. The description adds the user-scoping constraint, which is valuable behavioral context. However, it does not disclose pagination behavior (despite the 'cursor' parameter), potential rate limits, or the fact that logs may be truncated. With annotations covering safety, this is adequate but not rich.
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, perfectly scoped sentence that conveys the core action and resource. No extraneous information. Ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three parameters (one required) and an output schema exists, the description should cover parameter semantics and usage context. It fails on parameter explanation and provides no usage guidelines. The output schema likely covers return structure, but the description's gaps make the tool incomplete for an agent.
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%, so the description must explain parameters. Only 'jobId' is implicitly clear from the resource name. The optional parameters 'limit' and 'cursor' are not mentioned, leaving their semantics entirely unspecified. This is a significant gap that hampers correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Retrieve' and the resource 'execution logs for a specific Jungle Grid job'. It adds a key constraint ('belonging to the authenticated user') that helps distinguish from potential admin-only tools. However, it does not explicitly differentiate from sibling tools like 'get_job' or 'get_artifact', preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'list_jobs' or 'get_job'. There is no mention of prerequisites, context, or any exclusion criteria, leaving the agent to infer usage solely from the tool name and description.
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?
The description confirms destructive behavior ('may stop active execution'), aligning with annotations (destructiveHint=true). However, it does not elaborate on side effects like loss of outputs or irreversibility beyond what annotations provide.
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?
Single sentence, front-loaded with the verb 'Cancel'. No unnecessary words; every part serves the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with an output schema, the description is minimal but adequate. Could mention success/error behavior or state requirements for the job to be cancelable.
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 parameters 'jobId' or 'reason'. The description adds no meaning beyond the schema's property names and types.
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 'Cancel an existing Jungle Grid job' with a specific verb and resource. It distinguishes from siblings as the only cancel-related tool among list, get, submit, and estimate tools.
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 on when to use this tool versus alternatives like submitting a new job or estimating. The description lacks explicit context for when cancellation is appropriate.
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, which align with the description's 'Retrieve' action. The description adds no further behavioral context (e.g., authentication, error handling). With annotations covering safety, a score of 3 is appropriate.
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?
Single sentence, no filler, immediately conveys the tool's core action. Perfectly concise for a simple retrieval tool.
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?
Output schema exists but is not visible; the description could clarify what 'download information' includes (URL, size, etc.). Given 2 required params and no nested objects, the description is minimally sufficient but leaves ambiguity about the return value.
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 'jobId' or 'artifactId' parameters or their formats. It simply repeats the noun 'specific output artifact', adding no semantic value over the schema property names.
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?
Description clearly states the verb 'Retrieve' and the resource 'download information for a specific output artifact from a Jungle Grid job'. It distinguishes from siblings like 'list_artifacts' (list artifacts) and 'get_job' (get job info).
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?
Description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, limitations, or comparisons to siblings like 'list_artifacts' or 'get_job_logs'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-read-only and non-destructive. The description adds important behavioral context: starting infrastructure and incurring charges, which goes beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences with no redundancy. Every word adds value.
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?
Despite having an output schema and 9 parameters, the description provides minimal context. It lacks parameter guidance, error handling, or return value details, making it insufficient for a complex submission tool.
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 has 0% description coverage for 9 parameters. The description does not explain any parameter's meaning or usage, leaving the agent to infer from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the action ('Submit') and the resource ('Jungle Grid workload for execution'), clearly distinguishing it from siblings like cancel_job or get_job.
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 hints at when to use (for submission) and warns about potential charges and infrastructure startup, but does not explicitly compare to alternatives or state when not to use.
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds that the tool lists 'output artifacts', which provides minor context beyond annotations. No additional behavioral traits (e.g., pagination, errors) are disclosed.
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 of 10 words. It is front-loaded and contains no fluff, making it highly concise and 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 straightforward listing tool with one parameter and an output schema, the description adequately covers the basic purpose. It could be more complete by mentioning that it returns all artifacts for the job (no pagination implied). Still, it is sufficient given the tool's simplicity.
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 0%, so the description must compensate. It explains that the jobId parameter refers to a 'specific Jungle Grid job', but does not elaborate on format or source. For a single required parameter, this is marginal compensation.
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 'list', the resource 'output artifacts', and the scope 'associated with a specific Jungle Grid job'. It distinguishes from siblings like get_artifact (single artifact) and list_jobs (list of jobs).
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 list artifacts for a given job, but does not explicitly state when to or not to use this tool versus alternatives such as get_artifact for a single artifact. No exclusions or alternative tools are mentioned.
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?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds 'belonging to the authenticated user' (auth constraint) and specifies 'status and execution details' as return content. No contradiction, but marginal additional value.
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?
One sentence with clear verb-object structure, no filler, directly conveys essential information.
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?
Output schema exists, so return values are documented externally. Description covers purpose and auth constraint. Annotations provide safety profile. Complete for a simple read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the single parameter jobId is self-explanatory given its name and the tool's purpose. The description does not add extra detail about jobId format or constraints, but baseline 3 is appropriate for a simple, clear 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 specifies the verb 'Retrieve' and the resource 'specific Jungle Grid job', distinguishing it from siblings like list_jobs (list all) and cancel_job (cancel). It also adds scope 'belonging to the authenticated user'.
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 use for retrieving a specific job's status/details, but lacks explicit guidance on when to use vs alternatives (e.g., when to use get_job vs get_job_logs or list_jobs). No when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description need not reiterate safety. It adds value by specifying what the estimate covers (routing, capacity, cost). No contradictions with annotations. However, it omits details like rate limits or state effects, but these are less critical for a read-only estimate.
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, well-structured sentence with no filler. It front-loads the key action and resource, making it easy to process. Every word contributes to understanding.
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 8 parameters (1 required) and an output schema, the description covers the tool's purpose but lacks parameter guidance. The complexity is moderate, and while the output schema reduces the need to explain return values, the missing parameter semantics leave the description incomplete for correct invocation.
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 only 13% (only model_size described). The tool description does not elaborate on how parameters like workload, routing_mode, image, command, etc., affect the estimate. With low coverage, the description should compensate but fails to add meaningful parameter context, leaving parameters ambiguous.
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 ('Estimate'), the resource ('Jungle Grid workload'), and the specific aspects estimated ('routing, capacity source, expected cost'). It also distinguishes itself from submission tools by noting 'without submitting it', making the purpose very specific.
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 (before submission) versus the sibling 'submit_job'. However, it does not explicitly exclude cases like checking existing jobs or provide alternative contexts. While clear for its primary use case, additional guidance on when not to use it would improve this dimension.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds context about authentication and filtering, no contradictions.
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 sentences, front-loaded with action, no excess.
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?
Covers purpose and usage context, but lacks details on pagination parameters and response structure despite output schema existence.
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?
Only 'status' parameter is mentioned; 'limit' and 'cursor' (pagination) are not explained despite 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'list', resource 'Jobs for authenticated user', and optional filter by status. Differentiates from siblings like get_job and list_artifacts with usage tip.
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?
Explicitly advises using before status/log/artifact checks, but no explicit when-not-to-use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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