Fetch a docs markdown page by path (e.g. getting-started/installation, livewire, ai).
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Docs path without leading docs/, e.g. getting-started/installation or design-tokens |
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?
No annotations are provided, so the description must carry the behavioral disclosure burden. It states the tool fetches a markdown page, implying a read-only operationcolare. However, it does not mention potential error conditions (e.g., 404), return format specifics, or any prerequisites. For a simple read tool, this minimal disclosure is adequate but not thorough.
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 extremely concise, two phrases, front-loaded with the core action and path format examples. No wasted words.
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 the tool's simplicity, one parameter, no output schema, and full parameter documentation, the description is adequate. It could mention that the response is markdown content, but it's not critical for selecting this tool. A slight gap but overall complete.
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 schema description covers 100% of the parameter, so the parameter already has full documentation. The description adds only examples but no extra semantic nuance, so a baseline 3 is appropriate.
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 verb ('Fetch') and the resource ('a docs markdown page'), with concrete path examples (getting-started/installation, livewire, ai). It is easily distinguished from sibling tools like list_components or get_component_docs, which handle different kinds of content.
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 gives a clear action and example paths, but it does not explicitly state when to use this tool versus alternatives like get_component_docs or get_source. While the purpose implies usage for documentation pages, explicit guidance on exclusions or alternatives is missing, making it adequate but not exemplary.
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 are clearly distinct: component docs, component source, docs pages, and index browsing each target a specific need. The only potential confusion is between get_component_docs and get_docs_page, since component docs are a subset of docs pages, but the descriptions clarify the intended usage.
All tool names follow a consistent verb_noun pattern (get_* and list_*), with clear and predictable object nouns. This makes it easy to infer what each tool does before reading its description.
Six tools is well-scoped for a documentation and component lookup server. Each tool covers a distinct need—listing, fetching docs, fetching source, and browsing pages—without unnecessary duplication.
The core workflows of exploring components, fetching component docs, and retrieving source code are well covered. A minor gap is that blocks can only be listed, with no corresponding block detail or source tool, and there is no search capability beyond the llms.txt index.