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AWS MCP Server

by rishikavikondala
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dynamodb_update_ttl

Configure Time to Live (TTL) settings for DynamoDB tables to automatically expire items after a specified duration, managing data lifecycle and storage costs.

Instructions

Update the TTL settings for a table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYesName of the DynamoDB table
ttl_enabledYesWhether TTL should be enabled
ttl_attributeYesThe attribute name to use for TTL

Implementation Reference

  • src/mcp_server_aws/server.py:212-219 (handler)
    The core handler logic for the 'dynamodb_update_ttl' tool, which invokes the AWS DynamoDB client's update_time_to_live method with the provided table name, TTL enabled status, and attribute.
    elif name == "dynamodb_update_ttl":
    response = dynamodb_client.update_time_to_live(
        TableName=arguments["table_name"],
        TimeToLiveSpecification={
            'Enabled': arguments["ttl_enabled"],
            'AttributeName': arguments["ttl_attribute"]
        }
    )
  • src/mcp_server_aws/tools.py:401-422 (schema)
    Input schema and Tool definition for 'dynamodb_update_ttl', specifying parameters: table_name (string), ttl_enabled (boolean), ttl_attribute (string).
    Tool(
    name="dynamodb_update_ttl",
    description="Update the TTL settings for a table",
    inputSchema={
        "type": "object",
        "properties": {
            "table_name": {
                "type": "string",
                "description": "Name of the DynamoDB table"
            },
            "ttl_enabled": {
                "type": "boolean",
                "description": "Whether TTL should be enabled"
            },
            "ttl_attribute": {
                "type": "string",
                "description": "The attribute name to use for TTL"
            }
        },
        "required": ["table_name", "ttl_enabled", "ttl_attribute"]
    }
),
  • src/mcp_server_aws/server.py:136-140 (registration)
    Tool registration via the MCP list_tools handler, which returns get_aws_tools() containing the 'dynamodb_update_ttl' Tool object.
    async def list_tools() -> list[Tool]:
    """List available AWS tools"""
    logger.debug("Handling list_tools request")
    return get_aws_tools()

Tool Definition Quality

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Update' implies a mutation operation, but the description doesn't specify whether this requires specific permissions, if changes are reversible, potential impacts on existing data, or error conditions. For a mutation tool with zero annotation coverage, this leaves critical behavioral traits undocumented.

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 that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, with no redundancy or fluff.

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 mutation tool (updating TTL settings in DynamoDB) with no annotations and no output schema, the description is insufficient. It doesn't explain what TTL settings are, the implications of enabling/disabling TTL, expected return values, or error handling. For a tool that modifies database behavior, more context is needed for safe and effective use.

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 descriptions for all three parameters. The description adds no additional parameter semantics beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 ('Update') and resource ('TTL settings for a table'), making the purpose immediately understandable. It distinguishes from siblings like 'dynamodb_describe_ttl' (read vs. write) and 'dynamodb_table_update' (general vs. TTL-specific), though it doesn't explicitly name these alternatives. The description is specific but could be more precise about what TTL settings are being modified.

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. It doesn't mention prerequisites (e.g., table must exist), when to use 'dynamodb_table_update' for other settings, or when 'dynamodb_describe_ttl' might be needed first. Without such context, an agent must infer usage from the tool name and schema alone.

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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