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searchOrganizationContents

Search an organization's content database using semantic queries to locate relevant information efficiently.

Instructions

Search through the organization's content database using semantic search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query

Implementation Reference

  • mcp_server.py:58-72 (registration)
    Registration of the searchOrganizationContents tool in the list_tools() function, including its name, description, and input schema.
    types.Tool( name="searchOrganizationContents", description="Search through the organization's content database using semantic search", inputSchema={ "type": "object", "properties": { "query": { "type": "string", "description": "The search query" } }, "required": ["query"], "additionalProperties": False } ),
  • Input schema for the searchOrganizationContents tool, defining a required 'query' parameter of type string.
    inputSchema={ "type": "object", "properties": { "query": { "type": "string", "description": "The search query" } }, "required": ["query"], "additionalProperties": False }
  • The handler function implementing the core logic of the searchOrganizationContents tool by invoking RagService.search_contents with the query and user ID.
    def search_organization_contents(self, query: str) -> list[str]: """ Search through the organization's content database using semantic search. Args: query: The search query (required) Returns: List of search results """ return self.rag_service.search_contents(query, self.user_id_from_environment)
  • Dispatch logic in the call_tool handler that validates input and invokes the search_organization_contents method.
    elif name == "searchOrganizationContents": if "query" not in arguments: raise ValueError("Query parameter is required") result = rag_tools.search_organization_contents(arguments["query"]) logger.debug(f"Tool {name} executed successfully") return [types.TextContent(type="text", text=str(result))]

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