Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@wiring-diagram-mcp Size a 12V house bank for my campervan with 2 days autonomy"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
I refit my boat with Claude as the electrician. Here's the MCP that made it possible.
An MCP server that gives Claude (or any MCP-compatible AI) domain expertise in 12V / 24V / 48V electrical systems — sizing the bank, picking the wire gauge, recommending the fuse, and generating a complete wiring diagram. For boats, campers, vans, and off-grid builds.
{ "mcpServers": { "wiring-diagram": { "url": "https://mcp.voltplan.app/mcp" } } }Drop that into your claude_desktop_config.json, restart Claude, ask: "Plan a 400 Ah lithium house bank for a 30 ft sailboat with 2 days of autonomy." Done.
Built while refitting Largo, a 1996 Maxum, in Roermond. The math kept getting in the way of the work — sizing the bank, then the gauge, then the fuse, then redoing all of it after one load changed. So I gave Claude the math. Now it sizes the bank, picks the gauge, and generates the diagram. I'd rather just do the cabling.
The calculations are the same ones any cruiser or vanlifer ends up doing on graph paper at 11pm. This server makes them a one-sentence prompt.
Related MCP server: fronius-mcp
Nine tools, all callable by name from any MCP client:
Tool | What it does |
| Daily energy draw from a list of loads (Wh, Ah, peak power) |
| Bank size for given consumption + autonomy + DoD |
| Series/parallel arrangement to hit a target voltage and capacity |
| Panel wattage to recharge daily, accounting for sun hours and losses |
| AWG / mm² for current and run length, with fuse recommendation |
| Inverter wattage for AC loads, with surge headroom and DC current draw |
| Time from X% to Y% SoC, with bulk and absorption phases |
| Complete schematic as SVG or PNG, auto-fused and protected |
| Component reference and example configs for diagram building |
Three real prompts, three real outputs.
"Plan a 400 Ah lithium house bank for a 30 ft sailboat. Loads: 12V fridge 24/7 (60W), LED nav and cabin lights (25W, 4h/day), USB chargers (30W, 2h/day), occasional inverter for a laptop (90W, 3h/day). 2 days of autonomy without solar, LiFePO4 with 80% DoD."
Claude calls calculate_power_budget then calculate_battery_bank:
Total daily energy: 1,870 Wh/day (155.8 Ah/day at 12V)
Peak load: 205 W (17.1 A)
Required capacity (2 days × 80% DoD): 4,675 Wh / 389.6 Ah
Recommended bank: 4 × 100 Ah / 12.8 V LiFePO4 in parallel (4P)
Total / usable: 400 Ah / 5,120 Wh → 4,096 Wh usable
≈ 2.2 days of autonomy"What gauge wire for a 50A inverter run, 3 meters one-way, 12V, marine environment, max 3% drop?"
Claude calls calculate_wire_gauge:
Recommended cable: 16 mm² (6 AWG) — rated 65 A
Voltage drop: 0.34 V (2.80%) ✓ within target
Total resistance: 6.7 mΩ
Power lost as heat: 16.8 W
Fuse: 70 A ANL bolt-down, within 18 cm of battery+
Status: OK — wire size meets all requirements.(Ampacity alone would allow 10 mm² / 8 AWG, but voltage drop drives the choice up at this length.)
"Generate a wiring diagram for: 2 × 100W solar → MPPT → 200 Ah LiFePO4 → BMV-712 monitor → main 12V bus → fridge, lights, USB."
Claude calls generate_wiring_diagram and returns an SVG: batteries with terminals, MPPT charger, auto-generated shunt, main switch, low-voltage cutoff, and fused load lines in red/black with computed gauges.
See examples/ for five fully-worked scenarios — sailboat refit, Sprinter van, off-grid cabin, day sailer, live-aboard — each with the prompt, the expected tool calls, and the resulting numbers.
Edit claude_desktop_config.json (Settings → Developer → Edit Config):
{
"mcpServers": {
"wiring-diagram": {
"url": "https://mcp.voltplan.app/mcp"
}
}
}Restart Claude. The hammer icon in the chat input means tools are active.
{
"mcpServers": {
"wiring-diagram": {
"command": "npx",
"args": ["wiring-diagram-mcp"]
}
}
}# hosted
claude mcp add wiring-diagram --transport http https://mcp.voltplan.app/mcp
# local
claude mcp add wiring-diagram -- npx wiring-diagram-mcpEdit ~/.cursor/mcp.json (or .cursor/mcp.json per-project):
{
"mcpServers": {
"wiring-diagram": {
"url": "https://mcp.voltplan.app/mcp"
}
}
}Open the Cline panel → MCP Servers → Edit MCP Settings, then:
{
"mcpServers": {
"wiring-diagram": {
"url": "https://mcp.voltplan.app/mcp"
}
}
}npm install
npm run build
npm run start:http # listens on http://localhost:3001/mcpEnv var | Default | Purpose |
|
| VoltPlan instance for diagram rendering |
|
| HTTP server port |
docker build -t wiring-diagram-mcp .
docker run -p 3001:3001 wiring-diagram-mcp
Calculations run locally inside the MCP server (deterministic, no network). Diagram rendering hits the VoltPlan API and returns an SVG or PNG that the AI client embeds in the chat.
Worked scenarios in examples/:
AC-side calculations: shore power inlet, breaker panel sizing, isolation transformer
More battery chemistries: AGM/Gel sizing curves, lead-carbon
Multi-bank topologies: starter + house with combiner / DC-DC charger
Wire run optimization: shared trunks, terminal block placement
VoltPlan — web app for visual electrical system design
VoltPlan Wire Gauge Calculator — free, no signup
Built by Stefan Lange-Hegermann (yuzuhub.com). Powered by VoltPlan.
Issues, ideas, and pull requests welcome on GitHub.
MIT — see LICENSE.
Calculate the recommended battery bank size based on daily energy consumption. Accounts for days of autonomy (how many days without charging) and depth of discharge. Returns required capacity, number of batteries, and wiring configuration.
| Name | Required | Description | Default |
|---|---|---|---|
| dailyConsumptionWh | Yes | Daily energy consumption in watt-hours (from calculate_power_budget) | |
| daysOfAutonomy | No | Days the system should run without any charging (default: 2) | |
| depthOfDischargePercent | No | Usable percentage of battery capacity. LiFePO4: 80-90%, AGM: 50%, Gel: 50% (default: 80) | |
| systemVoltage | Yes | Target system voltage in volts (e.g. 12, 24, 48) | |
| singleBatteryAh | Yes | Capacity of a single battery in amp-hours (e.g. 100, 200) | |
| singleBatteryVoltage | Yes | Voltage of a single battery (e.g. 12.8 for LiFePO4, 12 for lead-acid) |
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.
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.
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.
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.
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.
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.
Determine how to arrange batteries in series and/or parallel to achieve a target voltage and capacity. Returns the number of batteries needed, the wiring configuration (e.g. 2S3P), and step-by-step wiring instructions.
| Name | Required | Description | Default |
|---|---|---|---|
| targetVoltage | Yes | Desired system voltage (e.g. 12, 24, 48) | |
| targetCapacityAh | Yes | Desired total capacity in amp-hours | |
| singleBatteryVoltage | Yes | Nominal voltage of one battery (e.g. 12.8 for LiFePO4, 12 for lead-acid, 3.2 for LiFePO4 cells) | |
| singleBatteryAh | Yes | Capacity of one battery in amp-hours |
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.
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.
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.
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.
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.
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.
Estimate how long it takes to charge a battery bank from a given state of charge to a target level. Accounts for the bulk charging phase (constant current, up to ~80% SoC) and the slower absorption phase (tapering current, 80-100% SoC). Works for any charging source: solar, shore power, alternator.
| Name | Required | Description | Default |
|---|---|---|---|
| batteryCapacityAh | Yes | Total battery bank capacity in amp-hours | |
| batteryVoltage | Yes | Battery bank voltage (e.g. 12, 24, 48) | |
| currentStateOfChargePercent | Yes | Current state of charge in percent (e.g. 20 for 20%) | |
| targetStateOfChargePercent | No | Target state of charge in percent (default: 100) | |
| chargePowerWatts | Yes | Charger output power in watts | |
| chargeCurrentAmps | No | Maximum charge current in amps (if limited by the charger or battery BMS). If omitted, calculated from power and voltage. |
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.
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.
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.
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.
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.
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.
Calculate the recommended inverter size for running AC loads from a DC battery system. Accounts for continuous power, startup surge power (motors typically surge 2-3x), and includes a 25% headroom for the continuous rating. Returns the recommended inverter wattage and the DC current draw at system voltage.
| Name | Required | Description | Default |
|---|---|---|---|
| systemVoltage | Yes | DC system voltage (e.g. 12, 24, 48) | |
| loads | Yes | List of AC loads that will run through the inverter |
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.
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.
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.
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.
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.
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.
Calculate total daily energy consumption from a list of electrical loads. Each load specifies its power draw, how many hours per day it runs, and quantity. Returns total daily energy (Wh and Ah), peak power draw, and average power. This is typically the first step in sizing a battery bank and solar system.
| Name | Required | Description | Default |
|---|---|---|---|
| systemVoltage | Yes | System voltage in volts (e.g. 12, 24, 48) | |
| loads | Yes | List of electrical loads to include in the budget |
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.
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.
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.
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.
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.
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.
Calculate the required solar panel wattage to cover daily energy consumption. Accounts for peak sun hours at the location and system efficiency losses (MPPT conversion, wiring, temperature derating). Returns required wattage and common panel configurations.
| Name | Required | Description | Default |
|---|---|---|---|
| dailyConsumptionWh | Yes | Daily energy consumption in watt-hours (from calculate_power_budget) | |
| peakSunHours | Yes | Average daily peak sun hours for the location. Examples: Northern Europe winter 1-2h, summer 4-6h. Southern US 5-6h. Equatorial regions 5-7h. | |
| systemEfficiency | No | Overall system efficiency factor (default: 0.85). Accounts for MPPT losses, wiring losses, temperature derating, and panel soiling. |
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.
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.
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.
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.
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.
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.
Calculate the recommended wire gauge / cable cross-section for a DC circuit. Considers both ampacity (current carrying capacity) and voltage drop to recommend the optimal cable size. Also returns total resistance, power loss, and a fuse recommendation. Supports copper conductors from 0.75 mm² (18 AWG) to 240 mm² (300 MCM).
| Name | Required | Description | Default |
|---|---|---|---|
| voltage | Yes | System voltage in volts (e.g. 12, 24, 48) | |
| current | No | Load current in amps. Provide either current or power. | |
| power | No | Load power in watts. Will be converted to current using the voltage. Provide either current or power. | |
| cableLengthM | Yes | One-way cable length in meters | |
| maxVoltageDropPercent | No | Maximum acceptable voltage drop in percent (default: 3%) | |
| temperatureCelsius | No | Ambient temperature in °C (default: 20°C). Affects copper resistance. | |
| isRoundTrip | No | Account for both positive and negative conductor (default: true). Set to false for chassis-ground returns. |
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.
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.
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.
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.
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.
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.
Generate an electrical wiring diagram for campers, boats, or off-grid setups. Returns a complete schematic with batteries, chargers, protection components, and loads. Protection components (shunt, main switch, low-voltage cutoff) are auto-generated when both batteries and loads are provided.
| Name | Required | Description | Default |
|---|---|---|---|
| systemName | Yes | Name of the electrical system (e.g. "My Camper Van") | |
| batteries | No | Batteries in the system | |
| loads | No | Electrical loads / consumers | |
| chargers | No | Chargers with their power sources | |
| format | No | Output format: svg (recommended, renders inline) or png (base64-encoded image, may not display in all clients) | svg |
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.
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.
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.
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.
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.
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.
List all available component types and example configurations for building wiring diagrams. Use this to understand what parameters are needed before calling generate_wiring_diagram.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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.
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.
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.
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.
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.
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.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.2.2calculate_battery_bankcalculate_battery_configcalculate_charging_timecalculate_inverter_sizecalculate_power_budgetcalculate_solar_sizecalculate_wire_gaugegenerate_wiring_diagramlist_component_typesEach 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.
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.
Nine tools cover the essential aspects of off-grid electrical system design without being excessive. Each tool serves a clear, needed function.
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.
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