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ScrapeBadger MCP Server

ScrapeBadger MCP Server

Official

github_get_repository

Fetch a public GitHub repository's default-branch details—statistics, topics, license, README, root files, and latest commit—by supplying owner and repo names, not a URL.

Instructions

Get a public GitHub repository on its default branch: statistics, topics, license, native README, root files and latest commit. Pass owner and repo separately, not a URL. 10 credits per successful uncached call.

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": {
      "owner": "<owner>",
      "repo": "<repo>"
    },
    "name": "github_get_repository"
  }
}

Input Schema

NameRequiredDescriptionDefault
repoYesRepository name, e.g. cli. Not a URL.
ownerYesOwner login, e.g. cli (owner.login from a profile repository summary).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose non-obvious traits: public-only scope, default-branch-only reading, a caching model, and a concrete cost of 10 credits per successful uncached call. It omits auth/prerequisite details and error behavior (404, private, rate limiting), which keeps it short of full disclosure.

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?

Two tight sentences: the first front-loads what is returned, the second covers input shape and cost. Every clause carries information and nothing is repeated.

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

Completeness4/5

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

There is no output schema, so the description compensates by enumerating the returned fields, plus cost and caching behavior. It lacks failure-mode guidance and any note on payload size or truncation (e.g., README/file contents), which would matter for a rich-detail fetch.

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

Parameters3/5

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

Schema description coverage is 100% and both parameters already document format, patterns, and 'Not a URL', so the baseline is 3. The description restates the same formatting rule ('pass owner and repo separately') without adding new syntax or constraints 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?

States a specific verb and resource ('Get a public GitHub repository') and immediately narrows scope to the default branch, then enumerates the payload (statistics, topics, license, README, root files, latest commit). No sibling tool in the list touches GitHub, so no differentiation is needed, and the agent can tell exactly what comes back.

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

Usage Guidelines4/5

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

Gives an explicit input convention ('Pass owner and repo separately, not a URL') that prevents a common misuse, and implicitly scopes usage to public repos. It does not state what to do when a repo is private or missing, so there is context but no exclusion/fallback guidance.

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