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Appwrite MCP Server

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by appwrite

tables_db_create_ip_column

Add an IP address column to a database table in Appwrite to store network identifiers, supporting optional arrays and default values.

Instructions

Create IP address column.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYesDatabase ID.
table_idYesTable ID.
keyYesColumn Key.
requiredYesIs column required?
defaultNoDefault value. Cannot be set when column is required.
arrayNoIs column an array?

Implementation Reference

  • The generic MCP tool handler that dispatches calls to all registered tools, including "tables_db_create_ip_column". It retrieves the bound method from the registry and executes it with the provided arguments, handling Appwrite-specific responses and errors.
    @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 name (e.g., 'tables_db_create_ip_column' from service_name 'tables_db' and method 'create_ip_column'), input schema from type hints and docstrings, and registers the bound function.
    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 service (aliased as 'tables_db'), which triggers automatic tool discovery and registration for all its public methods, including 'create_ip_column' becoming 'tables_db_create_ip_column'.
    def register_services(args):
        # If --all is specified, enable all services
        if args.all:
            args.tables_db = args.users = args.teams = args.storage = True
            args.functions = args.messaging = args.locale = args.avatars = True
            args.sites = True
    
        # Register services based on CLI arguments
        if args.tables_db:
            tools_manager.register_service(Service(TablesDB(client), "tables_db"))
        if args.users:
            tools_manager.register_service(Service(Users(client), "users"))
        if args.teams:
            tools_manager.register_service(Service(Teams(client), "teams"))
        if args.storage:
            tools_manager.register_service(Service(Storage(client), "storage"))
        if args.functions:
            tools_manager.register_service(Service(Functions(client), "functions"))
        if args.messaging:
            tools_manager.register_service(Service(Messaging(client), "messaging"))
        if args.locale:
            tools_manager.register_service(Service(Locale(client), "locale"))
        if args.avatars:
            tools_manager.register_service(Service(Avatars(client), "avatars"))
        if args.sites:
            tools_manager.register_service(Service(Sites(client), "sites"))
        if args.databases:
            tools_manager.register_service(Service(Databases(client), "databases"))
    
        # If no services were specified, enable tables_db by default
        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 adds a service's tools (generated by list_tools()) to the global tools_registry, making 'tables_db_create_ip_column' available to the MCP server.
    def register_service(self, service: Service):
        """Register a new service and its tools"""
        self.services.append(service)
        self.tools_registry.update(service.list_tools())
  • Imports the Appwrite TablesDB SDK class, whose methods (including create_ip_column) are wrapped as MCP tools.
    from appwrite.services.tables_db import TablesDB
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Create IP address column,' which implies a write/mutation operation, but doesn't mention permissions, side effects (e.g., impact on existing data), error conditions, or response format. This leaves significant gaps for a tool that modifies database structure.

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 a single, efficient sentence with zero waste—'Create IP address column.' It's front-loaded and appropriately sized for its limited content, though this conciseness contributes to gaps in other dimensions.

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?

Given the complexity of a database mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., what happens on creation, error handling), usage context, and return values, making it inadequate for safe and effective tool invocation.

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 fully documents all 6 parameters (e.g., database_id, table_id, key). The description adds no parameter-specific information beyond implying the column type is IP address, which is redundant with the tool name. This meets the baseline for high schema coverage.

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

Purpose3/5

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

The description 'Create IP address column' states the action (create) and resource type (IP address column), but it's vague about the context (database/table) and doesn't differentiate from sibling tools like 'tables_db_create_boolean_column' or 'tables_db_create_string_column' beyond specifying the column type. It lacks the specificity needed for clear sibling differentiation.

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?

No guidance is provided on when to use this tool versus alternatives like other column-creation tools (e.g., for different data types) or general table operations. The description implies usage for IP address columns but offers no context about prerequisites, constraints, or when not to use it.

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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