Fetch one full documentation page as Markdown, including resolved parameter tables and curl examples. Use a 'Page:' URL or path returned by search_docs or get_endpoint, e.g. '/docs/api/cars/inventory/inventory-search'. UK pages are under '/uk/docs/...'.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Docs path starting with /docs or /uk, or a full https://docs.marketcheck.com URL. |
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 covered. The description adds useful return-format context (Markdown, resolved tables, curl examples) and the UK path nuance, but does not expose deeper behavioral details like pagination or errors. This is acceptable given the read-only annotations.
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 tightly written sentences convey purpose, return format, valid input sources, an example, and the UK-path exception without redundancy. Every clause adds useful 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?
For a single-parameter, read-only fetch tool with no output schema, the description is complete: it explains what the tool returns, what input to pass, how to obtain that input, and a region-specific variant. Nothing essential for calling it correctly 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?
The schema already documents the single path parameter at 100% coverage. The description adds extra meaning by specifying the path should be a 'Page:' path from search_docs or get_endpoint and gives a concrete example, which helps the agent construct valid input beyond the raw schema text.
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?
States a specific verb and resource ('Fetch one full documentation page as Markdown') and adds distinctive details (resolved parameter tables, curl examples). The input-source note distinguishes it from siblings like search_docs and get_endpoint, so an agent can tell what this tool uniquely does.
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 clear context on what input to use: a 'Page:' URL or path returned by search_docs or get_endpoint, with an explicit example and UK-path variant. It does not explicitly state when not to use this tool versus each sibling, but the differentiation is mostly inferable from the description.
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.
Each tool has a distinct role: semantic search, listing endpoints, fetching endpoint reference, fetching doc pages, and retrieving plan/limit info. get_doc_page and get_endpoint could seem close, but the descriptions clearly separate full pages from exact endpoint references.
All tool names follow a predictable verb_noun pattern in snake_case: get_doc_page, get_endpoint, get_plans_and_limits, list_endpoints, search_docs. The verbs vary by action but are semantically appropriate and consistent in style.
Five tools is well-scoped for a documentation server. Each tool covers a necessary access pattern without redundancy or bloat.
The set covers the full documentation workflow: semantic search over all docs, enumeration of endpoints, exact endpoint details, full page retrieval, and current plan/limit data. There are no obvious dead ends for common documentation queries.