wiring-diagram-mcp

Server Quality Checklist

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Latest release: v0.2.2
Disambiguation5/5
Each tool targets a distinct calculation or generation task for electrical system design, such as battery sizing, inverter sizing, wiring diagram creation, etc. There is no overlap in purpose.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (e.g., calculate_battery_bank, generate_wiring_diagram, list_component_types), making it easy to predict tool behavior from names.
Tool Count5/5
Nine tools cover the essential aspects of off-grid electrical system design without being excessive. Each tool serves a clear, needed function.
Completeness4/5
The tool set covers the main workflow: power budget, battery/solar/inverter sizing, wire gauge, and diagram generation. Minor gaps exist, such as lack of AC wire sizing or load editing, but core needs are met.
Average 4.1/5 across 9 of 9 tools scored.
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 is passing
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.
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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?
With no annotations, the description alone must disclose behavior. It states the tool accounts for losses and returns wattage and configurations, implying a read-only calculation. However, it does not explicitly state that no data is modified, nor does it discuss authentication or side effects. Reasonable for a calculator but could be more explicit.
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 extremely concise with two sentences, no filler. First sentence presents the core purpose, second adds key details. Every word earns its place.
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?
The tool has no output schema, so the description must convey return format. It only says 'returns required wattage and common panel configurations' without details on structure. Given 3 parameters and no annotations, the description is adequate but incomplete regarding output.
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 100%, and parameter descriptions are detailed (e.g., examples for peakSunHours). The description adds context about what the tool accounts for (peak sun hours, efficiency) but does not add significant meaning beyond schema. Baseline 3 is appropriate.
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 purpose: to calculate required solar panel wattage based on daily consumption, peak sun hours, and system efficiency. This is a specific verb+resource pair that distinguishes it from sibling tools like calculate_power_budget or calculate_battery_bank.
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 for sizing solar panels after obtaining daily consumption, but it does not explicitly state when to use versus alternatives, nor does it mention prerequisites or when not to use. Two sentences provide context but lack explicit guidance.
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 should disclose behavioral traits. It mentions outputs (capacity, number, wiring) but lacks info on whether it's read-only, requires permissions, or has side effects. Adequate but could be more transparent.
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. First states purpose, second details inputs and outputs. Very concise and front-loaded with key information. No unnecessary words.
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 6 parameters and no output schema, the description adequately explains what the tool calculates and returns. Missing usage guidance relative to siblings, but the core functionality is well-covered.
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 100%, so the burden on the description is lower. The description adds context for 'daysOfAutonomy' and 'depthOfDischargePercent' by explaining their relevance, but adds minimal value for other parameters. Baseline 3 is appropriate.
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 purpose: calculate battery bank size from daily energy consumption. It mentions key factors (autonomy, depth of discharge) and outputs (capacity, number of batteries, wiring config). Distinguishes from siblings like calculate_battery_config by focusing on sizing.
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?
No explicit guidance on when to use this tool versus alternatives like calculate_battery_config. The description implies usage context (requires daily consumption) but does not mention prerequisites or 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?
The description discloses that it accounts for bulk and absorption phases, but lacks details on limitations (e.g., battery chemistry, temperature effects, assumed charge profile). With no annotations, the description carries full burden but is not fully transparent.
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: one for purpose, one for behavioral detail and scope. No unnecessary words, front-loaded with key information.
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?
The description covers the core functionality and scope, but lacks details on output format, edge cases, or assumptions. For a tool with 6 parameters and no output schema, it is adequate but not complete.
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 100%, so parameters are already well-documented. The description adds context about charging phases but does not enhance parameter meaning beyond 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 clearly states the tool estimates charging time for a battery bank from a given state of charge to a target level, using specific verbs and resources. It distinguishes from sibling tools focused on battery sizing, solar sizing, etc.
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 mentions it works for any charging source (solar, shore, alternator) and accounts for charging phases, giving context on when to use. However, it does not explicitly state when not to use or mention alternatives.
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 states the tool calculates and returns configuration details, which implies a read-only, deterministic operation. However, it does not disclose any assumptions (e.g., ideal batteries, rounding) or edge cases. Given the calculator nature, a 3 is baseline.
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, no filler. Front-loaded with purpose and immediate output details. Every sentence adds 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?
The tool has no output schema, so the description must explain return values. It does so (number of batteries, wiring config, instructions). It could mention handling of fractional numbers or rounding, but overall sufficient for a simple calculator.
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 100% with all parameters described. The description adds minimal meaning beyond the schema, just implying arrangement (series/parallel). Baseline 3 is appropriate.
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 'Determine how to arrange batteries' and resource 'battery config'. It specifies the outputs: number of batteries, wiring configuration (e.g., 2S3P), and step-by-step instructions, distinguishing it from sibling tools like calculate_battery_bank and generate_wiring_diagram.
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 use when needing to achieve a target voltage and capacity with given battery specs. While not explicit, the context of sibling tools (charging time, inverter size, etc.) helps differentiate. A 4 is appropriate as it is clear but lacks explicit when-not-to-use guidance.
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?
Without annotations, the description carries the full burden. It discloses that the tool accounts for continuous power, startup surge power (with typical multiplier), and a 25% headroom. It also states the return values (recommended wattage and DC current). This is good transparency for a calculator tool, though it could mention if any default assumptions are made about inverter efficiency.
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 extremely concise: two sentences, no wasted words. It front-loads the purpose and immediately follows with behavioral details. Every sentence earns its place.
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?
With 100% schema coverage and no output schema, the description adequately covers inputs and outputs. It explains the main calculation factors (surge, headroom) and what is returned (wattage, current). However, it does not mention edge cases or failure modes (e.g., invalid voltage), which would push it to 5.
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?
Schema coverage is 100% (baseline 3). The description adds significant value beyond the schema by explaining how parameters are used: 'Accounts for continuous power, startup surge power... includes a 25% headroom'. This gives the AI agent meaningful context about the calculation logic.
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 'Calculate' and the resource 'inverter size', and specifies the context: 'running AC loads from a DC battery system'. This distinguishes it from sibling tools like calculate_battery_bank or calculate_solar_size, which have different purposes.
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?
The description does not provide explicit guidance on when to use this tool versus its siblings. For example, it doesn't state that this should be used after determining battery capacity or solar size. The tool's purpose is understandable from context, but the lack of explicit usage hints limits its helpfulness for an AI agent.
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 provided, the description carries the full burden. It discloses the return values (daily energy, peak power, average power), which adds behavioral insight beyond the input schema. The tool is a calculation with no side effects, and the description implies read-only behavior.
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, concise and front-loaded with the core purpose. Every sentence adds value without redundancy.
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 has two parameters (one nested) and no output schema. The description covers the purpose and return values adequately. It does not address edge cases or validation, but for a straightforward calculation, it is sufficiently complete.
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 100%, so the schema already fully describes parameters. The description adds some context by mentioning 'power draw, hours per day, quantity' but does not significantly enhance understanding beyond the schema. Baseline 3 is appropriate.
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 calculates total daily energy consumption from a list of electrical loads, specifying the outputs (Wh, Ah, peak power, average power). This distinguishes it from sibling tools like calculate_battery_bank or calculate_solar_size, which serve different purposes.
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 explicitly states that this tool is 'typically the first step in sizing a battery bank and solar system,' providing clear usage context. It does not mention when not to use or alternative tools, but the context is sufficient.
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?
Discloses key behavioral traits: considers ampacity and voltage drop, returns resistance, power loss, and fuse recommendation. No annotations provided, so description carries the burden and does so adequately, though a note that it is read-only could be implied.
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?
Three sentences, no wasted words. First sentence captures the primary purpose, subsequent sentences add key details without extraneous information.
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?
No output schema, but the description lists what the tool returns (recommended gauge, resistance, power loss, fuse recommendation). It also states the conductor range. This is sufficient for a utility tool, though a bit more detail on the output format could help.
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?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining that it supports copper conductors from 0.75 mm² to 240 mm² and mentions the dual input of current or power, which enhances understanding 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?
Clearly states the tool calculates recommended wire gauge/cable cross-section for DC circuits, specifying the resource and verb. Differentiates from sibling tools that focus on batteries, solar, inverters, etc.
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?
Describes the context for usage (DC circuits, ampacity and voltage drop considerations). No explicit exclusion or alternative guidance, but the context is clear enough for an AI agent to infer appropriate use cases.
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 full burden. It discloses auto-generation of protection components and output format limitations (png may not display in all clients). However, it does not mention other behaviors like diagram topology or component placement.
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?
Three sentences, front-loaded with purpose, then output content, then specific behavior. No fluff; every sentence earns its place.
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 has 5 parameters and no output schema. The description lists what the schematic includes (batteries, chargers, protection, loads) and mentions format options. It could be more specific about output structure (e.g., labeled connections), but is sufficient for understanding.
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?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining parameter interplay (auto-generation condition) and summarizing the output, complementing the detailed 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 uses a specific verb ('Generate') and resource ('electrical wiring diagram'), and clearly states the domains (campers, boats, off-grid setups). It distinguishes itself from sibling calculation tools by focusing on diagram generation.
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 usage for generating visual schematics, contrasting with sibling calculate_* tools, but does not explicitly state when to use or exclude alternatives. It provides a conditional guideline (auto-generation when both batteries and loads are provided).
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 zero-parameter listing tool, no negative behavioral traits are expected. The description honestly states it lists 'all available' component types and example configurations. Additional detail on output format would improve transparency.
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, front-loaded with the action, and no redundant information. Every sentence serves a purpose.
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 description provides sufficient context given the tool's simplicity and zero parameters. However, it does not specify the return format, which could help agents anticipate output structure.
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?
With no parameters and 100% schema coverage, the description adds value by explaining the tool's purpose but does not need to elaborate on parameters. The baseline for zero-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 lists all available component types and example configurations for building wiring diagrams. It distinguishes itself from sibling calculation tools by focusing on listing and preparation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises to use this tool before calling generate_wiring_diagram to understand required parameters, providing clear usage guidance and context.
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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