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monacloud-mcp

monacloud-mcp

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by mona-software
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Công cụ MONA app logs

vibecloud_app_logs
Read-onlyIdempotent

Read deployment logs for a git app to diagnose build or runtime issues; returns up to 500 lines and may contain secrets, so avoid publishing raw output.

Instructions

Alias tương thích của cloud_app_logs. / Compatibility alias. App từ git đã live: app host đầu tiên ~2–3 phút, deploy sau đó 10–20 giây. / Git apps are live. Đọc tối đa 500 dòng log; có thể chứa secret, không đưa nguyên log ra công khai. / Read deployment logs.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "app_id": "<app_id>"
    },
    "name": "vibecloud_app_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
app_idYes
sandboxNoThử 0đ, không tạo hạ tầng thật / Sandbox, no charge
deploymentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.11.0

TDQS

B3.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnly/idempotent/non-destructive), the description adds real behavioral context: a 500-line read cap, that logs may contain secrets and should not be published verbatim, and git-app live timing (~2-3 min for first host, 10-20s for later deploys). These are substantive disclosures the annotations do not cover.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The content earns its place, but every sentence is delivered twice (Vietnamese then English), doubling the length without adding information. It is not bloated artificially, just redundant by format.

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 low-complexity read tool whose annotations already cover safety, the secrets warning and line limit are adequate. However, the two undescribed parameters and the incomplete alias relationship leave gaps an agent must guess at.

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?

With only 33% schema coverage (only 'sandbox' is documented), the description must carry the burden for app_id and deployment, yet it never mentions any of the three parameters. No added meaning over the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a clear verb+resource ('Read deployment logs') and explicitly frames the tool as a compatibility alias of the sibling cloud_app_logs. An agent can tell what it does, though the bilingual duplication muddies the front-loading.

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?

Calling it a 'compatibility alias' of cloud_app_logs implicitly tells the agent the two are interchangeable, but there is no explicit when-to-use-this-vs-the-other, no exclusions, and no prerequisites stated. Usage is only implied.

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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