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JIRA Zephyr MCP Server

by leorosignoli

list_test_plans

Retrieve existing test plans from a JIRA project to view available testing strategies and organize test cycles.

Instructions

List existing test plans

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectKeyYesJIRA project key
limitNoMaximum number of results (default: 50)
offsetNoNumber of results to skip (default: 0)

Implementation Reference

  • Core handler function that executes the list_test_plans tool logic: validates input with Zod, calls ZephyrClient.getTestPlans, maps and returns results or error.
    export const listTestPlans = async (input: ListTestPlansInput) => {
      const validatedInput = listTestPlansSchema.parse(input);
      
      try {
        const result = await getZephyrClient().getTestPlans(
          validatedInput.projectKey,
          validatedInput.limit,
          validatedInput.offset
        );
        
        return {
          success: true,
          data: {
            total: result.total,
            testPlans: result.testPlans.map(plan => ({
              id: plan.id,
              key: plan.key,
              name: plan.name,
              description: plan.description,
              status: plan.status,
              createdOn: plan.createdOn,
              updatedOn: plan.updatedOn,
              createdBy: plan.createdBy.displayName,
            })),
          },
        };
      } catch (error: any) {
        return {
          success: false,
          error: error.response?.data?.message || error.message,
        };
      }
    };
  • Zod schema definition for listTestPlans input validation, used in the handler.
    export const listTestPlansSchema = z.object({
      projectKey: z.string().min(1, 'Project key is required'),
      limit: z.number().min(1).max(100).default(50),
      offset: z.number().min(0).default(0),
    });
  • src/index.ts:91-103 (registration)
    Tool registration in the TOOLS array, defining name, description, and JSON input schema for MCP clients.
    {
      name: 'list_test_plans',
      description: 'List existing test plans',
      inputSchema: {
        type: 'object',
        properties: {
          projectKey: { type: 'string', description: 'JIRA project key' },
          limit: { type: 'number', description: 'Maximum number of results (default: 50)' },
          offset: { type: 'number', description: 'Number of results to skip (default: 0)' },
        },
        required: ['projectKey'],
      },
    },
  • MCP server dispatch handler for 'list_test_plans': validates args using Zod schema and delegates to listTestPlans function.
    case 'list_test_plans': {
      const validatedArgs = validateInput<ListTestPlansInput>(listTestPlansSchema, args, 'list_test_plans');
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(await listTestPlans(validatedArgs), null, 2),
          },
        ],
      };
    }
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 action ('List') but does not mention critical details such as whether this is a read-only operation, pagination behavior (implied by limit/offset but not explained), error conditions, or authentication needs. This leaves significant gaps in understanding how the tool behaves.

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 extremely concise with a single sentence ('List existing test plans'), which is front-loaded and wastes no words. It efficiently communicates the core purpose without unnecessary elaboration, making it easy to parse quickly.

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 tool's complexity (a list operation with parameters), lack of annotations, and no output schema, the description is incomplete. It fails to explain return values, error handling, or behavioral nuances, relying solely on the input schema. For a tool with no structured behavioral hints, this leaves the agent under-informed.

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?

The input schema has 100% description coverage, clearly documenting all three parameters (projectKey, limit, offset) with their types and defaults. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for adequate but not enhanced coverage.

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

Purpose3/5

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

The description 'List existing test plans' clearly states the verb ('List') and resource ('test plans'), making the purpose understandable. However, it lacks specificity about scope (e.g., all test plans vs. filtered) and does not differentiate from sibling tools like 'list_test_cycles' or 'search_test_cases', leaving room for ambiguity.

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 like 'search_test_cases' or 'list_test_cycles'. The description implies usage for listing test plans but offers no context on prerequisites, exclusions, or specific scenarios, leaving the agent to infer based on tool names alone.

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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