AgentSkillsCN

mcp-deepwiki

通过 DeepWiki 的 AI 驱动知识库,访问并查询 GitHub 仓库文档。提供 3 种工具,用于浏览文档结构、查看内容,以及提出问题。

SKILL.md
--- frontmatter
name: mcp-deepwiki
description: Access and query GitHub repository documentation using DeepWiki's AI-powered knowledge base. Provides 3 tools for browsing documentation structure, viewing content, and asking questions.
allowed-tools: Bash, Read

DeepWiki

Access and query GitHub repository documentation using DeepWiki's AI-powered knowledge base. Provides structured documentation browsing, content viewing, and natural language Q&A for any public GitHub repository.

Version: 0.0.1 (locked 2026-01-20)

When to Use This Skill

Use this skill when you need to:

  • Explore documentation structure of a GitHub repository
  • Read comprehensive documentation about a GitHub project
  • Ask specific questions about a repository's features, architecture, or usage
  • Understand unfamiliar libraries or frameworks through AI-assisted documentation

Tools

ToolDescription
read_wiki_structureGet a list of documentation topics for a GitHub repository
read_wiki_contentsView documentation about a GitHub repository
ask_questionAsk any question about a GitHub repository

⚠️ Always check tools/ for exact parameter names before calling.

Usage

Quick Start

⚠️ Before calling any tool, read its documentation in tools/ to get the exact parameter names.

bash
# List available tools and their schemas
node ./scripts/mcp-caller.mjs list

# Then check tools/<tool-name>.md for parameter details

CLI (Single Call)

Run from this skill directory:

bash
node ./scripts/mcp-caller.mjs call <tool> '<json-args>'
node ./scripts/mcp-caller.mjs resource <uri>
node ./scripts/mcp-caller.mjs prompt <name> '<json-args>'
node ./scripts/mcp-caller.mjs list

Programmatic (Batch/Parallel)

For batch operations or complex logic, use the API module:

javascript
// example.mjs - Run from this skill directory
import { callTool, listTools } from './scripts/api.mjs';

// First, check available tools and their schemas
const tools = await listTools();
console.log(tools.map(t => ({ name: t.name, params: Object.keys(t.inputSchema?.properties || {}) })));

// Then call with correct parameters (see tools/*.md for details)
const result = await callTool('toolName', { /* check tools/toolName.md for params */ });

// Parallel calls
const results = await Promise.all([
  callTool('tool1', { /* params from tools/tool1.md */ }),
  callTool('tool2', { /* params from tools/tool2.md */ }),
]);

console.log(JSON.stringify(results, null, 2));

Available API functions:

  • callTool(name, args) - Call a tool
  • listTools() - List available tools (includes inputSchema with parameter info)
  • readResource(uri) - Read a resource
  • listResources() - List resources
  • getPrompt(name, args) - Get a prompt
  • listPrompts() - List prompts
  • close() - Close connection (optional cleanup)

Error Handling

If a tool call fails (e.g., "method not found", parameter changes):

  1. Try to complete the task using other available tools
  2. Inform user: "This skill may be outdated - MCP server API has changed"
  3. User needs to run mcp-skill-generator to update this skill

Do not retry failed calls repeatedly - prioritize finding alternatives.

Updating

To update this skill with newer MCP server version:

  1. Run mcp-skill-generator
  2. Provide this skill's path for update