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ai-zerolab

MCP Email Server

by ai-zerolab

list_available_accounts

Retrieve all configured email accounts with masked credentials to manage email services and automate workflows.

Instructions

List all configured email accounts with masked credentials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'list_available_accounts' tool. It is decorated with @mcp.tool, which also serves as the registration. It retrieves the settings and returns a list of masked AccountAttributes for all configured email accounts.
    @mcp.tool(description="List all configured email accounts with masked credentials.")
    async def list_available_accounts() -> list[AccountAttributes]:
        settings = get_settings()
        return [account.masked() for account in settings.get_accounts()]
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It mentions 'masked credentials', which implies security measures, but doesn't detail other behaviors like read-only nature, potential rate limits, or response format. It adequately indicates a listing operation but lacks depth on operational traits.

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 a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action and includes a useful detail about credential masking, making it highly concise and well-structured.

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 the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete. It explains what the tool does and adds security context. However, it could benefit from more behavioral details, such as whether it's safe for frequent use or if it requires specific permissions.

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?

The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description doesn't add parameter details, which is appropriate. A baseline of 4 is applied as it compensates for the lack of parameters by focusing on the tool's purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('all configured email accounts'), making the purpose evident. It adds specificity with 'masked credentials' to indicate security handling. However, it doesn't explicitly differentiate from sibling tools like 'list_emails_metadata', which might list emails rather than accounts.

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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention if this should be used before 'add_email_account' to check existing accounts or as a prerequisite for other email operations. The description lacks context on usage scenarios or exclusions.

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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