Returns the authenticated tenant's customized theme tokens, CSS variables export, and component overrides. Call after auth to apply tenant-specific styling in generated code.
| 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?
With no annotations, the description carries the full burden. It discloses the type of data returned (tokens, CSS variables export, component overrides) and notes the dependency on authentication. It doesn't mention side effects, but the read-only nature is implied by 'Returns,' and the description adds useful context beyond just the tool name.
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 two efficient sentences: the first states exactly what the tool does, the second provides the usage context. Every word earns its place, with no filler or redundancy. It is front-loaded with the most important information.
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?
Given zero parameters and no output schema, the description provides sufficient context: it names the three types of outputs and the timing (after auth). This is complete for an agent to select and invoke the tool correctly, especially compared to similar tools in the catalog.
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, so the baseline is 4. The description correctly avoids inventing parameter details and instead focuses on the output. No additional parameter explanation is needed or expected.
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 exact purpose: returning the authenticated tenant's customized theme tokens, CSS variables export, and component overrides. The verb 'Returns' plus the specific resource (tenant's theme) makes it unambiguous and distinguishes it from sibling tools like get_design_guidelines or get_pattern.
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 says 'Call after auth to apply tenant-specific styling in generated code,' which provides a clear usage context (after authentication for styling in generated code). It doesn't explicitly exclude alternatives or name when not to use it, so a small gap remains, but the guidance is specific enough for most agents.
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 distinct purposes, but review_generated_code and validate_component_usage are very similar in functionality, differentiated only by intended usage context. list_components and search_components also have some overlap, though descriptions clarify their preferred use cases.
All tool names follow a consistent verb_noun snake_case pattern (e.g., get_component_info, list_components, review_generated_code). The verbs are clear and the naming convention is uniform throughout.
14 tools is well within the ideal 3-15 range and each tool serves a distinct role in the workflow: discovery, guidance, generation, validation, and prototype sharing. The count feels appropriate for the server's comprehensive purpose.
The server covers the full generation workflow: discover components, get guidelines, generate code, validate, and deploy/share. However, there is no tool to retrieve or list saved custom components, and prototype management is limited to deploy and feedback, leaving minor gaps in persisted resource handling.