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BhaumikAbhishek

OCI Kafka MCP Server

oci_kafka_create_cluster

Create a new OCI Apache Kafka cluster with configurable broker count, storage, and Kafka version to meet production or development needs.

Instructions

Create a new OCI Streaming with Apache Kafka cluster.

Requires --allow-writes. This is a HIGH RISK operation that requires confirmation. The operation is asynchronous — use oci_kafka_get_work_request to track progress.

Args: display_name: Human-readable name for the cluster. compartment_id: OCI compartment OCID where the cluster will be created. subnet_id: OCI subnet OCID for the cluster's private network. broker_count: Number of broker nodes (default: 3). kafka_version: Kafka version to deploy (default: 3.6.0). cluster_type: PRODUCTION or DEVELOPMENT (default: PRODUCTION). ocpu_count: OCPUs per broker node (default: 2). storage_size_in_gbs: Storage per broker in GB (default: 50). cluster_config_id: Optional OCID of a cluster configuration to apply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subnet_idYes
ocpu_countNo
broker_countNo
cluster_typeNoPRODUCTION
display_nameYes
kafka_versionNo3.6.0
compartment_idYes
cluster_config_idNo
storage_size_in_gbsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description discloses important behaviors: it requires --allow-writes, is high risk, and is asynchronous. It also directs the user to a progress-tracking tool. This adds value beyond the schema, but could further explain recovery steps or cost implications.

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 well-structured: a clear first sentence, followed by key warnings, then a bullet list of parameters. Every sentence adds value, though the parameter list could be slightly more concise by grouping defaults.

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

Completeness4/5

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

Given no annotations, the description covers the core purpose, risk, async nature, and all parameters. It does not describe the output schema, but per rules, that is acceptable since an output schema exists. It is sufficiently complete for an AI agent to use the tool correctly.

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

Parameters5/5

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

The input schema has 0% description coverage (only titles and defaults). The description compensates by listing all 9 parameters with clear, human-readable explanations of their purpose, adding significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a new OCI Streaming with Apache Kafka cluster. The verb 'Create' and the resource 'cluster' are specific, and the tool is distinct from siblings like update, delete, scale, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes that it requires --allow-writes, is a high-risk operation requiring confirmation, and is asynchronous with a recommendation to use oci_kafka_get_work_request for progress tracking. This provides context for safe usage, though it does not explicitly contrast with when to use alternative tools.

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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