Returns connection status and URLs. When all providers are connected, returns authenticated:true and empty pending[]. When credentials are missing, returns connect_url for the toolkit and per-install URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value beyond those annotations by explaining the two concrete return-state behaviors: fully connected returns authenticated:true with empty pending[], and missing credentials returns connect_url plus per-install URLs.
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 with no filler. The main purpose is front-loaded, and the conditional return behavior is clearly and compactly explained.
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?
For a zero-parameter, no-output-schema tool, the description covers the main behavioral cases: connected versus missing credentials. It could mention partial connection states or the exact shape of pending[], but the description is sufficiently complete for a simple status check.
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?
The input schema has zero parameters, so the baseline is 4. There are no parameters for the description to clarify, and it correctly focuses on behavior and return states instead.
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 opens with a specific verb and resource: 'Returns connection status and URLs.' It clearly distinguishes itself from siblings like authenticate by describing a read-only status/URL-reporting behavior rather than an authentication flow.
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 the tool is for checking connection status and retrieving URLs when credentials are missing, but it does not explicitly state when to use this tool versus alternatives like authenticate. There is no direct when-to-use or when-not-to-use guidance, only an implied context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The Plaud-specific tools are clearly distinct, but 'marketplace' is a mega-tool that appears to cover search, invoke, install, subscribe, prompts, and bug reporting — overlapping with connect, toolkit_info, and the standalone report_bug tool. An agent could easily pick the wrong entry point for connection status, installed tools, or feedback.
There is a clean plaud_get_* / plaud_list_* cluster, but the platform tools mix verbs and nouns: authenticate, connect, marketplace, report_bug, show_version, toolkit_info. The naming is readable and the Plaud prefix helps, but the overall pattern is inconsistent.
Eleven tools is a reasonable count and mostly well-scoped for a Plaud integration plus MCP platform management. It is slightly heavy because 'marketplace' bundles many sub-capabilities into one tool while several small utility tools exist separately.
The Plaud retrieval surface covers user, recordings, recording details, transcript, and AI notes, which is sufficient for the main use case of accessing Plaud data. Minor gaps exist around delete/update operations, but recordings are created externally by the hardware, so read-focused coverage is acceptable.