get_project_assetGet the asset (website/product) associated with a project — URL, name, description, solution profile.
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes | One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose. | |
| projectId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / contextAdded value: +{
+ "description": "One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose.",
+ "type": "string"
+}Input schema / requiredPrevious value: -[
- "projectId"
-]New value: +[
+ "projectId",
+ "context"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes that the call is safe, and the description adds what the caller will receive: URL, name, description, and solution profile. This is useful because there is no output schema to carry that information.
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?
A single front-loaded sentence with no filler; the core action and return fields are in the first clause. All content earns its place.
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 operation with only two parameters, the description provides enough information to understand the return value, and the schema handles the parameters. It could be more complete by clarifying what 'solution profile' means or how the context parameter affects the call, but nothing critical is missing.
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?
Schema description coverage is 50%: context has a description, but projectId only has a UUID format/pattern. The tool description adds no explanation of either parameter, though projectId is largely self-explanatory and context is already documented.
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 uses a specific verb-resource pair ('Get the asset ... associated with a project') and enumerates the returned fields (URL, name, description, solution profile). This differentiates it from sibling retrieval tools like get_project or get_project_overview by targeting the website/product asset rather than generic project data.
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 guidance is given about when to call this tool rather than get_project, get_page_dossier, or update_asset_profile. The description states only what the tool does, not the conditions or exclusions that should route an agent to it.
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 target a distinct resource and action, and the descriptions carefully cross-reference close alternatives (e.g., add_article_suggestion vs create_article_suggestion_with_input vs accept_idea). A few brief/read variants like get_article_brief, get_write_handoff, and download_brief_markdown could still be confused despite helpful explanations, so the set is not perfectly unambiguous.
Tool names follow a highly consistent verb_noun snake_case pattern throughout: get_*, list_*, create_*, update_*, set_*, add_*, delete_*, start_*, expand_*, etc. Even the less common names like lint_draft and remap_asset are still clear verb_noun constructions.
At 57 tools, this far exceeds the 50+ extreme threshold for a single MCP server. Even for a broad content workflow, the surface is overwhelming and would benefit from consolidation or splitting into focused servers.
The tool set covers the full content lifecycle: project setup, research runs, opportunity clustering, suggestion creation, brief generation, drafting, linting, publishing, reporting, and account management. Minor gaps exist—destinations and projects cannot be deleted via MCP, and there is no direct update for article suggestion metadata—but these are workable via the web UI or existing tools.