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Python

delete_sql_processor

Remove SQL processors from Kafka environments to manage data processing resources. Specify environment and processor ID to delete.

Instructions

Removes an existing SQL processor.

Args: environment: The environment name. sql_processor_id: SQL processor unique identifier.

Returns: Success message confirming the deletion.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
environmentYes
sql_processor_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/lenses_mcp/tools/sql_processors.py:92-105 (handler)
    The core handler function for the 'delete_sql_processor' tool. It constructs the API endpoint and performs a DELETE request via api_client to remove the specified SQL processor.
    @mcp.tool()
async def delete_sql_processor(environment: str, sql_processor_id: str) -> str:
    """
    Removes an existing SQL processor.
    
    Args:
        environment: The environment name.
        sql_processor_id: SQL processor unique identifier.
    
    Returns:
        Success message confirming the deletion.
    """
    endpoint = f"/api/v1/environments/{environment}/proxy/api/v1/streams/{sql_processor_id}"
    return await api_client._make_request("DELETE", endpoint)
  • src/lenses_mcp/server.py:32-32 (registration)
    Registers the SQL processors tools, including 'delete_sql_processor', by calling the register_sql_processors function with the MCP instance.
    register_sql_processors(mcp)
  • src/lenses_mcp/server.py:16-16 (registration)
    Imports the register_sql_processors function used to register the delete_sql_processor tool.
    from tools.sql_processors import register_sql_processors

Tool Definition Quality

C2.9/5.0
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 the tool is destructive ('Removes'), which is clear, but lacks critical details: whether deletion is irreversible, if it requires specific permissions, what happens to associated resources, or any rate limits. The description adds minimal value beyond the obvious destructive nature.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, with the core purpose stated first. The Args and Returns sections are structured clearly, though they could be more integrated. Every sentence earns its place, but minor improvements in flow (e.g., merging sections) could enhance readability without adding waste.

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

Completeness3/5

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

Given the tool's complexity (destructive operation with 2 parameters), no annotations, and an output schema (which covers return values), the description is minimally adequate. It covers the basic action and parameters but lacks context on behavioral risks, usage prerequisites, and error handling. The output schema reduces the burden, but more guidance is needed for safe 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 0%, so the schema provides no parameter details. The description adds basic semantics by naming the parameters ('environment' and 'sql_processor_id') and implying their roles, but doesn't explain format (e.g., what constitutes a valid environment name or ID), sources (e.g., from 'list_sql_processors'), or constraints. It compensates partially but not fully for the schema gap.

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 tool's purpose with a specific verb ('Removes') and resource ('an existing SQL processor'), making it immediately understandable. It distinguishes from siblings like 'create_sql_processor' by focusing on deletion rather than creation. However, it doesn't explicitly differentiate from other deletion tools like 'delete_kafka_connector' beyond the resource type.

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., whether the SQL processor must be stopped first), nor does it reference sibling tools like 'list_sql_processors' for selection or 'get_sql_processor' for verification. Usage is implied through the action but lacks explicit context.

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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