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JFrog MCP Server

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by jfrog

jfrog_list_runtime_clusters

Retrieve a paginated list of all runtime clusters on the JFrog Platform, with options to set limits and manage pagination for efficient cluster management.

Instructions

return a list of all my runtime clusters in the jfrog platform

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoThe maximum number of clusters to return
next_keyNoThe next key to use for pagination

Implementation Reference

  • Handler function for the jfrog_list_runtime_clusters tool that validates input and delegates to getAllRuntimeClusters API function
    handler: async (args: any) => {
      const parsedArgs = getAllRuntimeClustersSchema.parse(args);
      return await getAllRuntimeClusters(parsedArgs.limit);
    }
  • Zod input schema defining parameters for listing runtime clusters: limit (default 50) and optional next_key for pagination
    export const getAllRuntimeClustersSchema = z.object({
      limit: z.number().int().default(50).describe("The maximum number of clusters to return"),
      next_key: z.string().optional().describe("The next key to use for pagination")
    });
  • Helper function that performs the actual API call to list runtime clusters using jfrogRequest and parses the response with the response schema
    export async function getAllRuntimeClusters(limit:number) {
      const response = await jfrogRequest("/runtime/api/v1/clusters",{
        method: "POST",
        body: {
          limit
        }
      });
       
      return JFrogRuntimeClustersListResponseSchema.parse(response);
    }
  • tools/runtime.ts:90-94 (registration)
    Module-level registration of runtime tools array including the jfrog_list_runtime_clusters tool
    export const RuntimeTools = [
      getAllRuntimeClustersTool,
      getRuntimeClusterTool,
      listRunningImagesTool
    ];
  • tools/index.ts:13-23 (registration)
    Global tools registration array that includes RuntimeTools (containing jfrog_list_runtime_clusters) via spread operator
    export const tools =[
      ...RepositoryTools,
      ...BuildsTools,
      ...RuntimeTools,
      ...AccessTools,
      ...AQLTools,
      ...CatalogTools,
      ...CurationTools,
      ...PermissionsTools,
      ...ArtifactSecurityTools,
    ];
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 mentions 'return a list' but lacks details on permissions required, rate limits, pagination behavior (beyond implied by parameters), or response format. This is inadequate for a tool with potential operational impacts.

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, direct sentence with no wasted words, clearly stating the tool's purpose. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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 no annotations, no output schema, and a list operation with pagination parameters, the description is incomplete. It fails to address behavioral aspects like pagination handling, error conditions, or return structure, leaving gaps for effective tool use.

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 100%, so the schema fully documents the two parameters (limit and next_key). The description adds no additional parameter semantics beyond what's in the schema, such as default values or usage context, meeting the baseline for high schema coverage.

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 action ('return a list') and resource ('all my runtime clusters in the jfrog platform'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'jfrog_get_runtime_specific_cluster' or other list tools (e.g., 'jfrog_list_projects'), missing full sibling distinction.

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 instance, it doesn't mention when to choose this over 'jfrog_get_runtime_specific_cluster' or other list tools, nor does it specify prerequisites or exclusions, leaving usage context unclear.

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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