version: "1.0.1" name: knowledge-connect description: Analyze documents in your Yuque knowledge base, discover hidden connections between them (similar topics, complementary content), and suggest cross-reference links to build a knowledge network. For personal/individual use. license: Apache-2.0 compatibility: Requires yuque-mcp server connected to a Yuque account with personal Token metadata: author: chen201724 version: "1.0"

Knowledge Connect — Discover Links Between Your Notes

Analyze documents in your Yuque knowledge base, find hidden connections between them — similar topics, complementary content, shared concepts — and suggest cross-reference links to help you build a connected knowledge network.

When to Use

• User wants to find connections between their notes
• User says "帮我找找文档之间的关联", "哪些笔记是相关的", "connect my notes"
• User just finished writing a document and wants to link it to related ones
• User says "这篇文档和哪些笔记有关", "find related documents"
• User wants to build a knowledge graph from their existing notes

Required MCP Tools

All tools are from the yuque-mcp server:

• yuque_list_books — List user's knowledge bases
• yuque_list_docs — List all documents in a knowledge base
• yuque_get_doc — Read document content for analysis
• yuque_search — Search for potentially related documents
• yuque_update_doc — Add cross-reference links to documents

Workflow

Step 1: Determine the Scope

Ask the user what to analyze:

Case A — Single document: User provides a specific document link. Find connections for this one document.

Case B — Entire knowledge base: User specifies a knowledge base. Analyze all documents within it.

Case C — Across knowledge bases: User wants cross-repo connections. Analyze documents across multiple repos.

For Case B/C, first list available repos:

Tool: yuque_list_books

Then list documents in the target repo(s):

Tool: yuque_list_docs
Parameters:
  repo_id: "<namespace>"

Step 2: Analyze Documents

For each document in scope, fetch its content:

Tool: yuque_get_doc
Parameters:
  repo_id: "<namespace>"
  doc_id: "<slug>"

Extract the following from each document:

Step 3: Discover Connections

Compare documents pairwise and identify these types of connections:

For single-document analysis, also search for related documents:

Tool: yuque_search
Parameters:
  query: "[key topics from the document]"
  type: "doc"

Step 4: Present Connection Map

Present the discovered connections to the user:

## 🕸️ 知识关联分析
 
分析范围：[知识库名称] — [N] 篇文档
发现 [X] 组关联
 
### 关联 1：[主题/概念名称]
 
| 文档 | 关联类型 | 关联强度 |
|------|----------|----------|
| [文档 A 标题](链接) | 🔄 同主题 | ⭐⭐⭐ |
| [文档 B 标题](链接) | 🧩 互补 | ⭐⭐⭐ |
| [文档 C 标题](链接) | 🔗 共享概念 | ⭐⭐ |
 
**关联说明**：[为什么这些文档相关，它们之间的具体联系是什么]
 
**建议**：[具体的交叉引用建议，如 "在文档 A 的第二节末尾添加指向文档 B 的链接"]
 
### 关联 2：[主题/概念名称]
 
...
 
### 🏝️ 孤岛文档
 
以下文档暂未发现明显关联：
-[文档标题](链接) — 可能需要补充更多内容后再分析
 
### 💡 建议
 
1.[建议 1：如 "建议创建一篇索引文档，串联关于 X 主题的 5 篇笔记"]
2.[建议 2：如 "文档 A 和文档 B 观点互补，可以合并成一篇完整的指南"]

Step 5: Add Cross-References (Optional)

Ask the user: "要自动在相关文档中添加交叉引用链接吗？"

If confirmed, for each document that needs cross-references:

Tool: yuque_get_doc
Parameters:
  repo_id: "<namespace>"
  doc_id: "<slug>"

Append a "Related Notes" section at the end:

 
---
 
## 📎 相关笔记
 
-🔄 [相关文档标题](链接) — [一句话说明关联]
-🧩 [相关文档标题](链接) — [一句话说明关联]
 
*由 AI 分析生成的关联推荐 — YYYY-MM-DD*

Tool: yuque_update_doc
Parameters:
  repo_id: "<namespace>"
  doc_id: "<slug>"
  body: "<original content + related notes section>"

Confirm: "已为 [N] 篇文档添加了交叉引用链接 ✅"

Guidelines

• Always answer in the same language the user used (Chinese or English)
• Connection strength should be based on actual content overlap, not just title similarity
• Be specific about why documents are connected — vague "they're related" is not helpful
• Don't force connections — if two documents aren't meaningfully related, don't link them
• For large knowledge bases (> 50 docs), suggest analyzing in batches by topic area
• The "孤岛文档" section is valuable — it helps users identify notes that need more context
• When adding cross-references, never modify the original content — only append at the end
• Suggest creating index/hub documents for topics with 3+ related notes

Error Handling