validate_connector_configuration
Validate Kafka connector configurations to identify errors before deployment, ensuring proper integration with Lenses MCP Server environments.
Instructions
Validates a Kafka connector configuration.
Args: environment: The environment name. name: The name of the connector. cluster: The cluster name. configuration: The connector configuration to validate.
Returns: Validation results including configuration details and any errors.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| environment | Yes | ||
| name | Yes | ||
| cluster | Yes | ||
| configuration | Yes |
Implementation Reference
- The main handler function for the 'validate_connector_configuration' tool. It constructs a payload with name, cluster, and configuration, then makes a POST request to the /proxy/api/kafka-connect/validate endpoint to perform validation.async def validate_connector_configuration( environment: str, name: str, cluster: str, configuration: Dict[str, Any] ) -> Dict[str, Any]: """ Validates a Kafka connector configuration. Args: environment: The environment name. name: The name of the connector. cluster: The cluster name. configuration: The connector configuration to validate. Returns: Validation results including configuration details and any errors. """ payload = { "name": name, "cluster": cluster, "configuration": configuration } endpoint = f"/api/v1/environments/{environment}/proxy/api/kafka-connect/validate" return await api_client._make_request("POST", endpoint, payload)
- src/lenses_mcp/server.py:29-29 (registration)Registers the kafka_connectors tools, including 'validate_connector_configuration', by calling the register_kafka_connectors function on the MCP instance.register_kafka_connectors(mcp)