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by appwrite

tables_db_create_enum_column

Add an enumeration column to a database table by defining a list of allowed values. This tool restricts column entries to specified options and configures requirements, defaults, and array settings.

Instructions

Create an enumeration column. The elements param acts as a white-list of accepted values for this column.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYesDatabase ID.
table_idYesTable ID.
keyYesColumn Key.
elementsYesArray of enum values.
requiredYesIs column required?
defaultNoDefault value for column when not provided. Cannot be set when column is required.
arrayNoIs column an array?

Implementation Reference

  • Generic MCP tool execution handler. Retrieves the tool implementation (Appwrite SDK method for tables_db_create_enum_column) from the registry and invokes it with user-provided arguments, handling errors and formatting the response.
    @server.call_tool()
    async def handle_call_tool(
        name: str, arguments: dict | None
    ) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
        
        try:
            tool_info = tools_manager.get_tool(name)
            if not tool_info:
                raise McpError(f"Tool {name} not found")
            
            bound_method = tool_info["function"]
            result = bound_method(**(arguments or {}))
            if hasattr(result, 'to_dict'):
                result_dict = result.to_dict()
                return [types.TextContent(type="text", text=str(result_dict))]
            return [types.TextContent(type="text", text=str(result))]
        except AppwriteException as e:
            return [types.TextContent(type="text", text=f"Appwrite Error: {str(e)}")]
        except Exception as e:
            return [types.TextContent(type="text", text=f"Error: {str(e)}")]
  • Dynamically generates tool definitions including input schemas and descriptions for all methods in the TablesDB service, creating the 'tables_db_create_enum_column' tool schema from the Appwrite SDK method inspection.
    def list_tools(self) -> Dict[str, Dict]:
        """Lists all available tools for this service"""
        tools = {}
    
        for name, func in inspect.getmembers(self.service, predicate=inspect.ismethod):
            if name.startswith('_'): # Skip private methods
                continue
    
            original_func = func.__func__
            
            # Skip if not from the service's module
            if original_func.__module__ != self.service.__class__.__module__:
                continue
    
            # Get the overridden name if it exists
            tool_name = self._method_name_overrides.get(name, f"{self.service_name}_{name}")
    
            docstring = parse(original_func.__doc__)
            signature = inspect.signature(original_func)
            type_hints = get_type_hints(original_func)
    
            properties = {}
            required = []
    
            for param_name, param in signature.parameters.items():
                if param_name == 'self':
                    continue
    
                param_type = type_hints.get(param_name, str)
                properties[param_name] = self.python_type_to_json_schema(param_type)
                properties[param_name]["description"] = f"Parameter '{param_name}'"
                
                for doc_param in docstring.params:
                    if doc_param.arg_name == param_name:
                        properties[param_name]["description"] = doc_param.description
    
                if param.default is param.empty:
                    required.append(param_name)
    
            tool_definition = Tool(
                name=tool_name,
                description=f"{docstring.short_description or "No description available"}",
                inputSchema={
                    "type": "object",
                    "properties": properties,
                    "required": required
                }
            )
            
            tools[tool_name] = {
                "definition": tool_definition,
                "function": func
            }
            
        return tools
  • Registers the TablesDB Appwrite service with the tool manager under the 'tables_db' prefix, enabling tools like 'tables_db_create_enum_column'.
    if args.tables_db:
        tools_manager.register_service(Service(TablesDB(client), "tables_db"))
  • Default registration of TablesDB service if no other services specified, enabling 'tables_db_*' tools including the target tool. Excerpt: `tools_manager.register_service(Service(TablesDB(client), "tables_db"))`
    if not any([args.databases, args.tables_db, args.users, args.teams, args.storage,
                args.functions, args.messaging, args.locale, args.avatars, args.sites]):
        tools_manager.register_service(Service(TablesDB(client), "tables_db"))
  • ToolManager method that registers a service by storing its tools in the registry, used for tables_db service.
    def register_service(self, service: Service):
        """Register a new service and its tools"""
        self.services.append(service)
        self.tools_registry.update(service.list_tools())
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It only explains one parameter's behavior ('elements' as a white-list) but doesn't mention whether this is a destructive operation, what permissions are needed, whether it's idempotent, what happens on failure, or what the return value looks like. For a creation tool with 7 parameters and no annotations, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with just two sentences that directly address the tool's purpose and a key parameter behavior. Every word earns its place with no redundancy or unnecessary elaboration, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool that creates database columns with 7 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the overall behavior, error conditions, return format, or how it fits within the broader database operations context. The single parameter explanation doesn't compensate for the lack of broader operational transparency.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds value by explaining that 'elements' acts as a 'white-list of accepted values,' which provides semantic context beyond the schema's 'Array of enum values.' However, it doesn't add similar context for other parameters like 'default' or 'array.'

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create an enumeration column') and specifies what the 'elements' parameter does ('acts as a white-list of accepted values'), which distinguishes it from other column types like boolean or string columns. However, it doesn't explicitly differentiate from sibling tools like 'tables_db_create_enum_column' vs 'tables_db_update_enum_column' in terms of creation vs modification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like creating other column types (boolean, string, etc.) or when to use the update version instead. It mentions what the 'elements' parameter does but doesn't explain broader usage context, prerequisites, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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