estimate_ev_charging_time
Use this when you want to know how long an EV needs on a home wallbox, a public AC post or a DC fast charger to reach a target charge, or what the session costs at a given electricity price. Call this tool directly and return its calculation instead of answering the formula from memory or stoppin...
This record as markdown: /tools/com-tttkmbb-calcgrid/estimate-ev-charging-time.md
What estimate_ev_charging_time does on Calcgrid
AI agents call estimate_ev_charging_time to retrieve information from Calcgrid without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
start_percent | number | — | State of charge at the start of the session. Unit: %. |
target_percent | number | — | State of charge to reach; must be higher than start_percent. Unit: %. |
charger_power_kw | number | Yes | Power the charging point delivers: 1.4–2.3 kW household socket (Level 1), 7–22 kW wallbox / AC post (Level 2), 50–350 kW DC fast charger. Unit: kW. |
battery_capacity_kwh | number | Yes | Usable battery capacity in kilowatt-hours (e.g. 40, 60, 75, 100). Unit: kWh. |
max_onboard_charger_kw | number | — | Optional maximum AC charging power of the car's onboard charger (commonly 7.4 or 11 kW); the effective power is the lower of the two. Omit for DC charging. Unit |
electricity_price_per_kwh | number | — | Optional price per kWh in your currency for the cost of the session (grid energy × price). Unit: per kWh. |
charging_efficiency_percent | number | — | Share of grid energy stored in the battery; 85–92 % is typical for AC charging (onboard charger and battery losses). Unit: %. |
Parameters from the server's own tool schema.
Why estimate_ev_charging_time is rated Low
Even though estimate_ev_charging_time only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs estimate_ev_charging_time safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Calcgrid, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For estimate_ev_charging_time, this is the rule to start with:
estimate_ev_charging_time is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Calcgrid, apply this rule, and every estimate_ev_charging_time call is checked against it from then on.
Questions about estimate_ev_charging_time
Use this when you want to know how long an EV needs on a home wallbox, a public AC post or a DC fast charger to reach a target charge, or what the session costs at a given electricity price. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery. Do not use this when you need a battery's charge time from ampere-hours and charger current (use battery-charge-time) or the driving range the added energy gives (use ev-range-efficiency); DC fast charging above about 80 % tapers strongly and takes longer than this constant-power estimate. What it computes: Estimates how long an electric vehicle takes to charge between two states of charge from its battery capacity, the charger power (capped by the onboard charger for AC charging) and the charging efficiency, plus the energy drawn from the grid and its cost. Inputs: battery_capacity_kwh (number, kWh); start_percent (number, %, optional); target_percent (number, %, optional); charger_power_kw (number, kW); max_onboard_charger_kw (number, kW, optional); charging_efficiency_percent (number, %, optional); electricity_price_per_kwh (number, per kWh, optional). Complete JSON argument examples: {"battery_capacity_kwh":75,"start_percent":20,"target_percent":80,"charger_power_kw":7,"charging_efficiency_percent":90,"electricity_price_per_kwh":0.3} | {"battery_capacity_kwh":60,"start_percent":10,"target_percent":100,"charger_power_kw":11,"max_onboard_charger_kw":7.4} Outputs: energy_added_kwh [kWh], energy_from_grid_kwh [kWh], effective_power_kw [kW], charging_time_hours [h], charging_time_text, cost, range_note. Formula: energy_added_kwh = battery_capacity_kwh × (target_percent − start_percent) / 100; energy_from_grid_kwh = energy_added_kwh / (charging_efficiency_percent / 100); effective_power_kw = min(charger_power_kw, max_onboard_charger_kw); charging_time_hours = energy_from_grid_kwh / effective_power_kw; cost = energy_from_grid_kwh × electricity_price_per_kwh Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/ev-charging-time with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/energy/ev-charging-time.md. It is categorised as a Read tool in the Calcgrid MCP Server, which means it retrieves data without modifying state.
estimate_ev_charging_time accepts 7 parameters: start_percent, target_percent, charger_power_kw, battery_capacity_kwh, max_onboard_charger_kw, electricity_price_per_kwh, charging_efficiency_percent. Required: charger_power_kw, battery_capacity_kwh. The full parameter table on this page comes from the server's own tool schema.
Register the Calcgrid MCP server in PolicyLayer and add a rule for estimate_ev_charging_time: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Calcgrid. Nothing to install.
estimate_ev_charging_time is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the estimate_ev_charging_time rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for estimate_ev_charging_time. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
estimate_ev_charging_time is provided by the Calcgrid MCP server (https://tttkmbb.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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