Password Strength Scoring for AI Agents
The tool
Give enterprise agents password-strength scoring through the same data layer, rating complexity and weakness per request.
Once your client is connected to the VerveContext MCP server, this appears in its tool list as PasswordStrengthScoringforAIAgents. It is read-only and open-world: it fetches, it never mutates anything on your side, so most clients will call it without asking you to confirm.
{
"name": "PasswordStrengthScoringforAIAgents",
"arguments": {
"password": "Password123"
}
}What that looks like in a conversation
You don't name the tool — the model picks it. Asking about Password123 in the terms this source covers is enough for it to reach for PasswordStrengthScoringforAIAgents on its own.
Connecting
One server URL covers every source in the catalog, including this one. Authorization is OAuth — the client opens a browser once and there is no key to paste into a config file.
{
"mcpServers": {
"vervecontext": {
"url": "https://api.vervecontext.com/v1/mcp"
}
}
}https://api.vervecontext.com/v1/mcpPer-client setup — Claude Desktop, Cursor, VS Code, ChatGPT — is on the MCP setup page.
Arguments
These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made.
| Argument | Type | Example | Description |
|---|---|---|---|
passwordRequired | string | Password123 | The password to check the strength of |
What the model gets back
The result carries a structuredContent object matching the tool's declared outputSchema, so a client can read fields without parsing prose. status is "ok" on success and error is null; a null field means the value wasn't available for that input, not that the call failed.
{
"status": "ok",
"error": null,
"data": {
"strength": "weak",
"score": 1,
"passwordInfo": {
"length": 11,
"hasSpecialCharacters": false,
"hasNumbers": true,
"hasLowercase": true,
"hasUppercase": true,
"hasSpaces": false,
"hasSequentialChars": true,
"hasRepeatedChars": false
},
"recommendations": [
"Use at least 12 characters",
"Add special characters",
"Avoid sequential characters (e.g. abc, 123)"
],
"entropyBits": 65.5
}
}Fields
| Field | Type | Example | Description |
|---|---|---|---|
strength | string | Strength label: too weak, weak, medium or strong | |
score | number | Numeric strength score (0-3, higher is stronger) | |
passwordInfo | object | ||
└ passwordInfo.length | number | Number of characters in the password | |
└ passwordInfo.hasSpecialCharacters | boolean | Whether the password contains special characters | |
└ passwordInfo.hasNumbers | boolean | Whether the password contains numbers | |
└ passwordInfo.hasLowercase | boolean | Whether the password contains lowercase letters | |
└ passwordInfo.hasUppercase | boolean | Whether the password contains uppercase letters | |
└ passwordInfo.hasSpaces | boolean | Whether the password contains spaces | |
└ passwordInfo.hasSequentialChars | boolean | Whether the password contains a run of 3+ sequential characters (e.g. abc, 123) | |
└ passwordInfo.hasRepeatedChars | boolean | Whether the password repeats the same character 3+ times in a row (e.g. aaa) | |
recommendationsPremium | array | List of recommendations to improve password strength | |
entropyBitsPremium | number | Theoretical charset entropy in bits (length times log2 of the character-set size). This is the ceiling assuming random character selection; it does not account for dictionary words or common patterns, so use the strength/score for real-world guidance |
Why ground on it
A model can produce something that looks like this answer from its training data, and be confidently out of date or simply wrong. This source returns the current value with a shape you can check, which is the difference between an answer you can cite and one you have to hedge.
Point an evaluation at strength: it is the field most worth pinning a claim to, and it is either present and current or absent — never plausibly invented.
Failure modes
Errors come back as tool errors with a sentence the model can act on, not a bare status code.
| Status | What it means |
|---|---|
400 / 422 | The arguments didn't validate. The message names the offending one. |
401 | The OAuth session is invalid or expired — reconnect the server. |
403 | Out of credits. Not a bad key — the month's allowance is spent. |
404 | This source isn't part of VerveContext. Check the catalog. |
429 | Brief rate limit. Retrying after a moment succeeds. |
Other ways to use Password Strength Scoring for AI Agents
Set up Password Strength Scoring for AI Agents on VerveContext, or reach the same source a different way. Your VerveContext account and credits work on all of them — one key, one balance.
Frequently asked questions
Do I have to tell the agent to use PasswordStrengthScoringforAIAgents?
No. The tool's name and description are in the model's context once the server is connected, so it selects the tool when the question calls for it. Naming it explicitly works too and is useful when you want to force the call.
Does connecting the server expose every tool at once?
Yes — one connection lists the whole VerveContext catalog. Clients with a tool budget can usually filter the list; the credit cost is per call, so an unused tool costs nothing.
What does a call cost?
1 credit each time the tool actually runs. A model that reasons about the tool without calling it costs nothing.
Is there a REST version of this?
Yes — the same source is available as a plain HTTPS endpoint on APIVerve, linked above. Same data, same credits, same account.