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rishikavikondala

AWS MCP Server

by rishikavikondala
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Python
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dynamodb_table_list

List all DynamoDB tables in your AWS account to manage and monitor database resources.

Instructions

List all DynamoDB tables

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/mcp_server_aws/server.py:197-198 (handler)
    Executes the DynamoDB list_tables() operation to retrieve the list of all tables.
    elif name == "dynamodb_table_list":
    response = dynamodb_client.list_tables()
  • src/mcp_server_aws/tools.py:155-162 (schema)
    Defines the input schema (empty object since no parameters required) and metadata for the dynamodb_table_list tool.
    Tool(
    name="dynamodb_table_list",
    description="List all DynamoDB tables",
    inputSchema={
        "type": "object",
        "properties": {}
    }
),
  • src/mcp_server_aws/server.py:136-139 (registration)
    Registers the dynamodb_table_list tool (among others) with the MCP server by returning the list of AWS tools.
    async def list_tools() -> list[Tool]:
    """List available AWS tools"""
    logger.debug("Handling list_tools request")
    return get_aws_tools()

Tool Definition Quality

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. 'List all DynamoDB tables' implies a read-only operation, but it doesn't disclose behavioral traits like whether it requires specific IAM permissions, if it's paginated (likely for many tables), if it includes deleted tables, rate limits, or what the return format looks like. For a tool with zero annotation coverage, this is a significant gap.

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, clear sentence with zero waste: 'List all DynamoDB tables'. It's front-loaded and efficiently communicates the core purpose without unnecessary words. Every word earns its place.

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 (listing all tables in a cloud database service), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what information is returned (e.g., table names, ARNs, status), whether results are filtered or paginated, or any AWS-specific context like region scoping. For a tool in this context, more detail is needed.

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

Parameters4/5

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

The input schema has 0 parameters with 100% description coverage, so no parameters need documentation. The description doesn't add parameter information, which is appropriate here. A baseline of 4 is given since there are no parameters to explain, and the description doesn't create confusion by mentioning nonexistent parameters.

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 'List all DynamoDB tables' clearly states the verb ('List') and resource ('DynamoDB tables'), making the purpose immediately understandable. It distinguishes from siblings like dynamodb_table_describe (which describes a specific table) and dynamodb_table_create/delete/update (which modify tables). However, it doesn't explicitly mention that this lists tables across all regions or accounts, which could be implied but isn't specified.

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 when to use dynamodb_table_list versus dynamodb_item_query or dynamodb_item_scan for data retrieval, or versus dynamodb_table_describe for table metadata. There's no context about prerequisites, permissions needed, or typical use cases.

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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