Skip to main content
Glama
ahmedselimmansor-ctrl

IBM Cloud MCP Server

watson_create_space

Creates a Watson Machine Learning deployment space with specified name, description, compute instance, and region.

Instructions

Create a Watson deployment space

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo
compute_nameNoWML instance CRN
regionNo

Implementation Reference

  • MCP tool handler for 'watson_create_space' - accepts name, description, compute_name, and region; constructs the request body and POSTs to the WML v2/spaces endpoint.
    server.tool("watson_create_space", "Create a Watson deployment space", {
      name: z.string(), description: z.string().optional(),
      compute_name: z.string().optional().describe("WML instance CRN"), region: z.string().optional(),
    }, async (p) => safeTool(async () => { w();
      const body: Record<string,unknown> = {name:p.name, description:p.description};
      if(p.compute_name) body.compute=[{name:p.compute_name,type:"machine_learning"}];
      return client.post(`${ml(p.region||r)}/v2/spaces`, body, {version:ver});
    }));
  • Zod schema defining the input parameters for the watson_create_space tool: name (required), description (optional), compute_name (optional WML instance CRN), region (optional).
    name: z.string(), description: z.string().optional(),
    compute_name: z.string().optional().describe("WML instance CRN"), region: z.string().optional(),
  • Registration function that registers all Watson tools on the MCP server, including watson_create_space.
    export function registerWatsonTools(server: McpServer, client: IBMCloudAPIClient, config: ServerConfig) {
  • src/server.ts:68-69 (registration)
    Top-level call to registerWatsonTools which registers watson_create_space among all Watson tools.
    registerWatsonTools(server, client, config);
    console.error(`  ✓ Watson AI (8 tools)`);
  • Endpoint helper for constructing the Watson ML base URL based on region.
    WATSON_ML: (region: string) =>
      `https://${region}.ml.cloud.ibm.com`,
Behavior2/5

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

With no annotations, the description must disclose all behavioral traits, but it only states the basic create action. It does not mention permissions required, whether the operation is destructive (it likely is not), rate limits, or any side effects like automatic naming conventions. The single sentence is insufficient for safe agent usage.

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 a single sentence, which is appropriately concise and front-loaded. However, it sacrifices informational value for brevity; every sentence should earn its place, and this one does not provide enough information beyond the tool name.

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 (4 parameters, no output schema, no annotations), the description is too skeletal. It does not explain what a 'deployment space' is, what the return value might indicate (success/failure), or any required prior steps. The description is incomplete for effective tool usage.

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

Parameters2/5

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

The input schema has 4 parameters with only 25% description coverage. The description adds no further parameter explanations, such as acceptable formats for 'region' or the purpose of 'description'. Without additional context, the agent cannot discern meanings beyond the schema's sparse hints.

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 explicitly states the action 'Create' and the resource 'Watson deployment space', clearly distinguishing it from sibling tools like watson_list_spaces (which lists spaces) and watson_delete_deployment (which deletes deployments). The verb+resource combination is specific and unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives. For example, it does not mention that a space must exist before deploying models, nor does it provide any context about prerequisites or exclusions. The description lacks any usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ahmedselimmansor-ctrl/IBM_cloud_MCP_SERVER'

If you have feedback or need assistance with the MCP directory API, please join our Discord server