github-code-rag-mcp

web_search_github

Search GitHub repositories for open source projects using the official GitHub search page, bypassing rate limits without an API key.

Instructions

通过 GitHub 官方搜索页搜索开源项目（免费，无需 API Key，无限额度）。

当 search_github 限流时用这个替代。搜索 GitHub 上的仓库。解析 github.com/search 的 HTML 结果页，不依赖第三方搜索引擎。

Args: query: 搜索关键词 (如 "电商网站 React") limit: 返回结果数 (default: 10, max: 20)

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": {
      "query": "<query>"
    },
    "name": "web_search_github"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`query`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 19, 2026

TDQS

A4.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the mechanism (parsing HTML) and the free/unlimited nature, but doesn't mention potential rate limits on the HTML scraping itself, pagination behavior, or what happens if the HTML structure changes. It's adequate but not rich.

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

Conciseness4/5

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

The description is concise and front-loaded with the key purpose and advantage. The Args section is clear. Minor redundancy: '搜索 GitHub 上的仓库' repeats the purpose already stated, but overall it's efficient.

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?

Given the tool's moderate complexity (2 params, no annotations, output schema exists), the description covers the essential purpose, usage context, and parameter semantics. It doesn't describe the output structure, but the output schema exists, so that's acceptable. It could mention error cases (e.g., if search page is blocked) but is otherwise complete.

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 0%, so the description must compensate. It explains query as search keywords with an example, and limit as result count with default and max. This adds meaning beyond the bare schema, but doesn't specify the format of results or how limit interacts with pagination. Baseline 3 is appropriate.

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 searches GitHub open-source projects via GitHub's official search page, explicitly noting it's free, requires no API key, and has unlimited quota. It distinguishes itself from sibling tool search_github by being a fallback when rate-limited, and from search_code by targeting repositories rather than code.

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 explicitly says to use this tool when search_github is rate-limited, providing a clear alternative. It also clarifies it parses github.com/search HTML results and doesn't rely on third-party search engines, giving the agent context on when this is appropriate.

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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