MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
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 state idempotentHint=true and destructiveHint=false, so the description doesn't need to repeat that. It adds valuable behavioral context: the permanence of config-based auth versus session-only login, and that calling with no args returns a link. No contradictions with annotations; the description enhances transparency.
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?
The description is a single block of 2-3 sentences and is front-loaded with the core purpose. It covers both modes without excessive verbosity, though it could be tightened slightly (e.g., 'MCP.AI for IDE agents' is a bit odd). Overall, it's efficient and well-structured.
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 tool with one optional param and no output schema, the description fully covers the two invocation modes and what happens in each. It doesn't explain error handling or return format beyond getting a link, but that's acceptable given the simplicity. It's complete for the agent's needs.
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 schema provides only a bare 'token' string without description, and schema coverage is 0%. The description compensates by explaining the token parameter as a JWT for session-only login and describes the no-args behavior. It doesn't detail edge cases (e.g., invalid tokens) but gives enough for correct invocation.
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 clearly states the tool's purpose: to authenticate to the MCP server by either generating a login link (no args) or accepting a JWT token for session login. It explicitly identifies the resource (the server) and the action (authenticate), and distinguishes from siblings like connect by focusing on auth mechanics.
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?
It gives explicit when-to-use guidance: recommends adding the token to server config for permanent access, and offers session-only login via token pasting. Also specifies the exact call patterns (with token or no args) and the workflow for IDE agents (browser login, copy token). This covers both usage context and alternatives.
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 WHOOP data tools (whoop_body_measurement, whoop_cycles, whoop_recovery, etc.) are clearly distinct by metric type. The platform tools are mostly distinct, but authenticate and connect both deal with connection - authenticate handles token acquisition while connect checks status and provides URLs, which could cause some initial confusion. Marketplace is a large multi-purpose tool but is well-described.
The WHOOP-specific tools follow a consistent whoop_<noun> pattern (whoop_body_measurement, whoop_cycles, whoop_sleep), but the platform tools mix conventions: single-word nouns (connect, marketplace), camelCase-like snake_case (report_bug, show_version, toolkit_info), and bare verbs (authenticate). This inconsistency makes the naming less predictable.
13 tools is well within the ideal 3-15 range. The WHOOP data tools cover distinct health metrics, and the platform tools cover auth, connectivity, marketplace, version, and status. Each tool has a clear purpose and the count feels proportionate to the server's dual role as an MCP platform manager and WHOOP data provider.
The WHOOP data surface covers body measurements, daily cycles, recovery, sleep, workouts, profile, and account listing - comprehensive read access to WHOOP's core data. The platform side includes authentication, connection status, marketplace operations, bug reporting, version info, and toolkit state, forming a complete lifecycle for both the MCP platform and WHOOP data access.