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Appwrite MCP Server

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by appwrite

tables_db_get_column

Retrieve a specific column from an Appwrite database table by providing the database ID, table ID, and column key.

Instructions

Get column by ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYesDatabase ID.
table_idYesTable ID.
keyYesColumn Key.

Implementation Reference

  • Generic handler for all tools, including 'tables_db_get_column'. Retrieves the tool's 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 and input schemas for all service methods, including 'tables_db_get_column', using inspect, type hints, and docstrings.
    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 'tables_db' prefix, enabling dynamic tool registration for methods like get_column as 'tables_db_get_column'.
    if args.tables_db:
        tools_manager.register_service(Service(TablesDB(client), "tables_db"))
  • Default registration of the TablesDB service if no other services are specified.
            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 adding its tools to 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 but only states the basic action without disclosing behavioral traits such as whether it's read-only, requires permissions, returns metadata or data, or handles errors. 'Get' suggests a read operation, but details like response format or side effects are missing.

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 ('Get column by ID.') with no wasted words, making it front-loaded and easy to parse. It efficiently conveys the core purpose in a single sentence.

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 no annotations and no output schema, the description is incomplete for a tool with 3 parameters. It lacks context on what 'get' returns (e.g., column properties, data types), error handling, or how it fits with sibling tools, leaving gaps for an AI agent to infer behavior.

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%, with clear parameter descriptions in the input schema (e.g., 'Database ID', 'Table ID', 'Column Key'). The description adds no meaning beyond this, as it doesn't explain parameter relationships or usage. Baseline 3 is appropriate since the schema does the heavy lifting.

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 'Get column by ID' clearly states the action (get) and resource (column), but it's vague about what 'get' entails (e.g., retrieve metadata vs. data values) and doesn't distinguish from siblings like 'tables_db_get' or 'tables_db_list_columns'. It's functional but lacks specificity.

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 'tables_db_list_columns' (for listing all columns) or 'tables_db_get' (for general database retrieval). The description implies usage for fetching a specific column but offers no explicit context 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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