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DocsHub MCP Server

DocsHub MCP Server

by rkratky
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Fetch Project Documentation

get_project_docs
Read-onlyIdempotent

Fetch documentation for a project: retrieves complete docs via llms-full.txt, or an index of URLs via llms.txt if full text is not available. Use with project names from list_available_docs.

Instructions

Fetch documentation for a project.

Automatically tries llms-full.txt first, which returns the complete documentation in a single response — no further calls needed. If llms-full.txt is unavailable, falls back to llms.txt and returns an index of URLs; use read_doc_page with those URLs to retrieve individual pages.

Call list_available_docs first to get valid project names.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_name": "<project_name>"
    },
    "name": "get_project_docs"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_nameYesExact project name as returned by list_available_docs.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Even with readOnlyHint and idempotentHint annotations, the description adds valuable behavioral detail: it discloses the automatic fallback mechanism, the two possible return modes (complete documentation vs. URL index), and the dependency on a prior list_available_docs call. This goes well beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a clear opening sentence, followed by two short paragraphs explaining fallback and prerequisite. Every sentence contributes meaningful information without verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (one parameter) and the description explains both the primary behavior and the fallback path, including what to do with the fallback output. It covers the full call flow and the relationship to sibling tools, and the presence of an output schema further reduces the need to elaborate on return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter is well-documented in the schema ('Exact project name as returned by list_available_docs'), and the description reinforces this by stating to call list_available_docs first. Since schema coverage is 100%, the description adds modest but useful reinforcement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it fetches documentation for a project, with the specific verbs 'Fetch' and 'tries'. It also distinguishes itself from siblings by explaining the llms-full.txt vs llms.txt fallback and referencing read_doc_page and list_available_docs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to call list_available_docs first to get valid project names. Also describes when the fallback to llms.txt applies and directs the user to read_doc_page for individual pages, making the when-to-use and alternatives explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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