Read the storefront back, in the shape a machine reads it: name, tagline, links, offerings, sections and files. Takes no arguments. Your operator sees the same records rendered visually. Use it to check what you published.
| 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 and destructiveHint=false, so the safety profile is known. The description adds what the returned data looks like (fields and machine-readable shape), which is useful context beyond the annotation, but no further behavioral details like pagination or error cases.
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 redundancy. The first sentence conveys the resource and fields, the second gives purpose. Front-loaded and efficient.
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 simple read-only tool with no parameters, the description lists the returned fields and usage context. It lacks a detailed output schema description, but the field list compensates enough for an agent to understand what to expect. Minor gap: no mention of potential empty results or error behavior.
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?
There are 0 parameters, and the description explicitly states 'Takes no arguments', which aligns with the empty schema. Since there are no params, the description needs no further semantic elaboration; this statement is clear and matches the schema.
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?
Description states a specific verb 'Read' and resource 'storefront', and enumerates the exact fields (name, tagline, links, offerings, sections, files). It clearly distinguishes from the sibling storefront_set by implying a read-only operation.
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?
Provides a usage context: 'Use it to check what you published', which implies after a write operation. However, it does not explicitly name alternatives or when not to use, relying on the tool name to imply the counterpart.
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.
Most tools have clearly distinct purposes, but the deprecated tools (list_datasets, list_market_apis, search_datasets, try_dataset) overlap with modern replacements (search_catalog, get_listing). Some functional overlap exists between get_activity and charge_list, but descriptions clarify their scopes. Overall, an agent can usually tell tools apart, with a few legacy remnants.
Tool names follow a consistent snake_case verb_noun pattern (browse_catalog, business_start, charge_create, etc.). Even the deprecated tools adhere to the same style. There are no mixed conventions or vague verbs like 'process' or 'run'. The naming is highly predictable.
At 52 tools, this is a large surface. The domain is broad (marketplace buying/selling, business management, policy, storefront, distribution, authentication), so many tools are justifiable. However, four deprecated tools could be pruned, and the count is on the heavy side compared to typical MCP servers. It feels overengineered, yet each tool addresses a distinct facet of the platform.
The toolset covers the full lifecycle: discovery, evaluation, purchase, delivery, feedback, business management, policy, storefront, and distribution. Gaps are minor—for example, no direct way to list all services with full details without service_list, but that exists. The deprecated tools indicate ongoing migration to a consolidated search surface, suggesting good coverage. A few small gaps remain (e.g., no explicit 'update listing' for buyers, but that may not be needed).