get_trialGet the organization's trial: which tier it grants, whether it is still running, when it expires and how many days are left. Unlike the other billing tools this one only needs organization membership, not billing:read. Requires organization context. Read-only: plan, seat and top-up changes are not available through MCP by design — a human does those in the web app.
| 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?
The description explicitly states that the tool is read-only and that plan, seat, and top-up changes are not available through MCP, aligning with the readOnlyHint annotation. No side effects or contradictions are mentioned.
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 succinct and to the point, using three sentences to convey purpose, permission requirements, and read-only nature. It avoids unnecessary fluff while covering all essential details.
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?
The description provides sufficient context for a user to understand what the tool does, including its permission requirements and read-only nature. Despite lacking an output schema, the description is comprehensive enough for a zero-parameter read-only tool.
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 no parameters, so the description does not need to explain parameter meanings. The absence of parameters is clear and consistent, making this dimension trivially satisfied.
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: retrieving the organization's trial details including tier, status, expiration, and days remaining. It also distinguishes itself from other billing tools by noting it requires only organization membership, not billing:read.
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 explicitly explains when to use the tool (to get trial information) and contrasts it with other billing tools, clarifying that it does not require billing:read. It also notes the requirement for organization context, providing clear usage 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 tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.
All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.
With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.
The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.