get_document_chunks
Retrieve all text chunks from a document to analyze content structure. Provides chunk IDs, page numbers, and text summaries for comprehensive document examination.
Instructions
获取指定文档的所有 chunks 列表
根据 doc_id 获取该文档的所有文本块摘要信息。
Args: doc_id: 文档的唯一标识符
Returns: chunks 列表，每个包含 chunk_id、页码和文本摘要
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| doc_id | Yes |
Implementation Reference
- src/paperlib_mcp/tools/fetch.py:190-243 (handler)The handler function for the 'get_document_chunks' tool. It retrieves all chunks for a given document ID from the database, providing summaries including chunk_id, index, pages, token count, snippet, and embedding status.@mcp.tool() def get_document_chunks(doc_id: str) -> dict[str, Any]: """获取指定文档的所有 chunks 列表 根据 doc_id 获取该文档的所有文本块摘要信息。 Args: doc_id: 文档的唯一标识符 Returns: chunks 列表，每个包含 chunk_id、页码和文本摘要 """ try: chunks = query_all( """ SELECT c.chunk_id, c.chunk_index, c.page_start, c.page_end, c.token_count, LEFT(c.text, 100) as snippet, CASE WHEN ce.chunk_id IS NOT NULL THEN true ELSE false END as has_embedding FROM chunks c LEFT JOIN chunk_embeddings ce ON c.chunk_id = ce.chunk_id WHERE c.doc_id = %s ORDER BY c.chunk_index """, (doc_id,) ) return { "doc_id": doc_id, "chunk_count": len(chunks), "chunks": [ { "chunk_id": c["chunk_id"], "chunk_index": c["chunk_index"], "page_start": c["page_start"], "page_end": c["page_end"], "token_count": c["token_count"], "snippet": c["snippet"] + "..." if len(c["snippet"]) >= 100 else c["snippet"], "has_embedding": c["has_embedding"], } for c in chunks ], } except Exception as e: return { "error": str(e), "doc_id": doc_id, "chunks": [], }
- src/paperlib_mcp/server.py:36-36 (registration)Registers the fetch tools module, which includes the get_document_chunks tool, on the MCP server instance.register_fetch_tools(mcp)