keymaster-mcp

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find_credentials

Read-only

Locate stored credentials by URL, hostname, alias, or phrase when a login, API call, CLI/DB auth, or 2FA code is needed; returns ranked metadata-only matches and ambiguity flags.

Instructions

ALWAYS THE FIRST STEP when anything needs credentials — a login, an API call, a CLI or DB that needs auth, a 2FA code, or the user asking for a password/token/key. Pass whatever you have: a URL, hostname, name, alias or phrase ("https://ci.example.com/job/x", "jenkins", "prod db", "aws sg"). Returns ranked matches, metadata only (secrets hidden), and flags ambiguous when you should ask the user which one.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "find_credentials"
  }
}

Input Schema

Name	Required	Description	Default
`tag`	No
`type`	No
`limit`	No
`query`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Oct 7, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations only cover the safety profile (readOnly, non-destructive, closed-world), but the description adds return semantics an agent genuinely needs: ranked matches, metadata-only with secrets hidden, and an `ambiguous` flag that signals it should ask the user to disambiguate. That is real behavioral context beyond the structured fields.

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 tight sentences, front-loaded with the applicability rule, then input guidance, then return behavior. No filler; every clause carries information an agent would otherwise have to guess.

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 exists, and the description compensates by describing returns (ranked matches, metadata-only, ambiguity flag). It also handles the fuzzy-query contract well. The remaining gap is the undocumented optional filters (tag, type, limit), which an agent may not know it can use.

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 0%, so the description must carry parameter meaning. It does this well for `query` ('pass whatever you have' plus URL/hostname/name/alias/phrase examples), but says nothing about `tag`, `type`, or `limit`, leaving three of four params undocumented anywhere.

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?

States a specific verb+resource ('find credentials') and immediately scopes it as a ranked lookup rather than a list or fetch. The framing 'ALWAYS THE FIRST STEP when anything needs credentials' cleanly distinguishes it from siblings like list_credentials and get_credential, which are enumeration/retrieval tools.

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?

Gives concrete trigger scenarios (login, API call, CLI/DB auth, 2FA, user asking for a password/token/key) and instructs on input flexibility. It stops short of naming the alternatives (list_credentials, get_credential) or stating when NOT to use it, so the routing is strong but not exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.