get_membershipReturn Free and Founding Pro terms and available Stripe-hosted checkout URLs. Calling this tool does not open checkout or claim payment success.
| Name | Required | Description | Default |
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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?
The description adds a key behavioral guarantee beyond the annotations: 'Calling this tool does not open checkout or claim payment success.' This is valuable because Stripe URLs can easily be mistaken for triggering payment. Combined with readOnlyHint/idempotentHint, the agent understands the operation is side-effect-free.
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 deliver the core purpose, the exact data returned, and the critical behavioral caveat. No filler or redundant content; the most decision-relevant fact is front-loaded.
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, read-only tool, the description covers what is returned and the important non-effect. It does not explain the format of checkout URLs or whether terms are ever unavailable, but for this simple getter that is not a blocking gap.
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 tool has zero parameters, and the schema is completely minimal. Baseline for zero params is 4; there is nothing more the description needs to clarify about parameters, and it does not attempt to invent any.
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 states a specific verb ('Return') and a clear resource (membership terms, including Free and Founding Pro, plus Stripe checkout URLs). It is sufficiently precise that an agent can distinguish it from the sibling tools, which concer watches, editions, and events rather than membership.
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?
No explicit when-to-use or alternative-routing guidance is provided. The context of the sibling tools makes the intent fairly clear, and the tool's name plus description imply it is the go-to for membership terms, but the description does not state exclusions or conditions.
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 watch and edition tools are clearly distinct, but get_context and score_headline overlap heavily—both accept a headline, share the referenceContext parameter, and disclose withheld/conflicting info—and get_brief vs read_latest_edition both serve 'what's the latest news' requests. The verbose 'do not use for' guardrails in the descriptions help, but they also signal that the boundaries are not naturally obvious.
All names follow snake_case verb_noun, with predictable patterns: list_* for collections, create/update/acknowledge for watch mutations, read_* for editions. Minor inconsistency exists between get_brief and read_latest_edition (both fetch news content) and between get_membership and list_watches (both return list-like info), but the overall scheme is readable and consistent.
14 tools sits within the typical well-scoped band, and each tool appears to serve a real product feature. The surface is slightly broad for a 'news' server, spanning saved-watch management, edition reading/export, headline analysis, and membership/checkout, which makes it heavier than a focused news reader.
Edition access (list/read/export) and the analysis workflow (score/context/discover) are well covered, but the watch lifecycle has no delete_watch, leaving agents unable to remove saved watches—a real dead end. There is also no story-level read or search tool, though the descriptions explicitly scope that out.