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DocsHub MCP Server

DocsHub MCP Server

by rkratky
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Read Documentation Page

read_doc_page
Read-onlyIdempotent

Fetch Markdown content from a documentation page URL provided by an llms.txt index. Access specific developer docs for AI processing.

Instructions

Fetch the Markdown content of a specific documentation page.

Use URLs obtained from get_project_docs when it returns an llms.txt index. Do not call this if get_project_docs already returned complete documentation. Only URLs from configured project hosts are permitted.

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": {
      "url": "<url>"
    },
    "name": "read_doc_page"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesHTTPS URL of a documentation page from an llms.txt index.

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?

Beyond the readOnlyHint and idempotentHint annotations, the description adds key behavioral context: it fetches Markdown content, requires URLs from an llms.txt index, and enforces a security restriction on allowed hosts. This gives the agent a fuller picture of expected inputs and constraints without contradicting 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 compact and front-loaded with the core action. Every sentence adds value: the first defines what it does, the second gives sourcing guidance, and the third provides a critical security constraint. No wasted words.

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?

Given the simple single-parameter schema, complete schema coverage, and presence of an output schema, the description fully covers all essential context: when to call, what it fetches, and host restrictions. The tool is uncomplicated, and the description is complete for an agent to invoke it correctly.

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 schema already describes the 'url' parameter as an HTTPS URL from an llms.txt index, so the description does not need to repeat it. However, it adds provenance guidance by explicitly telling the agent to use URLs obtained from get_project_docs, which is valuable semantic context beyond the schema.

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 the tool fetches Markdown content for a specific documentation page, using an explicit verb and resource. It differentiates from siblings by referencing get_project_docs and specifying the page-level granularity, distinguishing this from listing or retrieving entire doc sets.

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?

The description gives explicit usage guidance: use URLs from get_project_docs when it returns an llms.txt index, do not call if complete documentation was already returned, and only permitted host URLs. This clearly indicates when to use the tool and when not to, fulfilling the dimension.

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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