Search Text in Document
search_textFind specific text strings in Markdown files and locate their structural positions using semantic search to identify content within document hierarchies.
Instructions
Performs a semantic search for text strings and returns their structural paths.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | ||
| query | Yes | String to search for |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| results | No | List of matching elements with their paths |
Implementation Reference
- Core implementation of search_text method in Document class. Recursively traverses the element tree to find elements containing the query string (case-insensitive) and returns list of dicts with path, type, and preview.
def search_text(self, query: str) -> List[Dict[str, Any]]: """Search text across all elements""" query = query.lower() results = [] def walk(elements): for el in elements: if query in el.content.lower(): results.append( {"path": el.path, "type": el.type, "preview": el.content[:100]} ) walk(el.children) walk(self.elements) return results - src/markdown_editor/server.py:110-139 (registration)Registers the search_text tool with the MCP server, defining its name, title, description, input schema (file_path and query), and output schema.
Tool( name="search_text", title="Search Text in Document", description="Performs a semantic search for text strings and returns their structural paths.", inputSchema={ "type": "object", "properties": { "file_path": { "type": "string", "examples": ["./document.md", "/path/to/file.md"], }, "query": { "type": "string", "description": "String to search for", "examples": ["TODO", "urgent", "deadline"], }, }, "required": ["file_path", "query"], "additionalProperties": False, }, outputSchema={ "type": "object", "properties": { "results": { "type": "array", "description": "List of matching elements with their paths", } }, }, ), - src/markdown_editor/server.py:566-573 (handler)Tool dispatch handler in server.py that calls search_in_document with file_path and query, formats the result with count, and returns as CallToolResult.
elif name == "search_text": res = await search_in_document(file_path, arguments["query"]) result = {"results": res, "count": len(res)} return CallToolResult( content=[TextContent(type="text", text=json.dumps(result, ensure_ascii=False, indent=2))], structuredContent=result, isError=False, ) - Helper method in EditTool class that loads the Document instance and delegates to its search_text method.
async def search(self, file_path: str, query: str) -> List[Dict[str, Any]]: doc = self.get_doc(file_path) return doc.search_text(query) - Top-level async wrapper function that invokes the singleton EditTool instance's search method.
async def search_in_document(file_path: str, query: str): return await _instance.search(file_path, query)