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mouldiwarp

solax-cloud-mcp

by mouldiwarp
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one retrieves real-time data, the other sets a battery mode. There is no ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun snake_case pattern (get_realtime_data, set_battery_self_use_mode), making them predictable.

    Tool Count2/5

    With only 2 tools, the server feels too thin. A typical solar inverter API would require more tools (e.g., historical data, other modes, configuration) to be useful.

    Completeness2/5

    Major gaps exist: no tool for reading current battery mode, no historical data, no other inverter settings. The set covers only real-time data and one battery mode.

  • Average 4.6/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 11 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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

  • Behavior4/5

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

    With no annotations, the description carries full burden. It discloses that the tool sends a command to the inverter, returns an API response, and raises ToolError for offline inverter, invalid credentials, or API failure. It does not detail potential side effects on other settings, but overall transparency is good.

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

    Conciseness4/5

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

    The description is structured with a one-line summary, explanatory paragraph, example scenarios, and a clear list of arguments. It is slightly verbose but front-loads the purpose. No unnecessary sentences, but could be trimmed slightly.

    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?

    Given 13 parameters, no output schema, and no annotations, the description covers all aspects: parameter details, error conditions, usage scenarios. It is comprehensive enough for an agent to invoke the tool correctly.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so description must compensate. It provides thorough details for all 13 parameters: defaults, ranges (e.g., min_soc [10,100]), formats (HH:MM for time periods), and explanations of each parameter's purpose. This fully compensates for the lack of schema descriptions.

    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 sets inverter battery to Self Use Mode with configurable thresholds. It uses a specific verb ('Set') and resource ('inverter battery'), and distinguishes from sibling tool get_realtime_data which is read-only.

    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 explains when Self Use Mode is ideal (automated control based on conditions) and provides example automation scenarios. It does not explicitly exclude other modes or provide alternatives, but given the sibling tool, context is clear. Score 4 for clear context without explicit exclusions.

    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?

    Describes the operation as read-only ('Fetch', 'Retrieves'), lists error conditions, and provides return structure details. No annotations are present, so description covers the behavioral aspects well.

    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?

    Well-structured with summary, units, clear Args/Returns/Raises sections. Front-loaded with main purpose, no superfluous content.

    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 single-parameter tool, the description fully covers input, output (detailed return structure), and error behavior, making it self-contained without needing an output schema.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Clearly explains the parameter 'device_sn', including the distinction from WiFi dongle SN and the default environment variable. This adds significant value beyond the schema which lacks descriptions.

    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 'Fetch real-time solar inverter data' with a specific data source. It distinguishes from the sibling tool 'set_battery_self_use_mode' which is a write operation.

    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?

    Provides context like data source and default environment variable, but lacks explicit when-to-use or when-not-to-use guidance relative to siblings.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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