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KS-GEN-AI

Jira MCP Server

by KS-GEN-AI

get_only_ticket_name_and_description

Extract ticket names and descriptions from Jira using JQL queries to quickly access essential issue details without markdown formatting.

Instructions

Get the name and description of the requested tickets on the api /rest/api/3/search/jql. Do not use markdown in your query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jqlYesJQL query string
number_of_resultsNoNumber of results to return

Implementation Reference

  • Handler implementation inside the MCP server request handler switch statement. Extracts JQL query and number of results, calls executeJQL helper, maps issues to only key, summary, and description, and returns formatted JSON.
    case 'get_only_ticket_name_and_description': {
      const jql = String(request.params.arguments?.jql);
      const number_of_results = Number(
        request.params.arguments?.number_of_results ?? 1,
      );
    
      if (!jql) {
        throw new Error('JQL query is required');
      }
    
      const response = await executeJQL(jql, number_of_results);
    
      // Return only the ticket name and description
      const tickets = response.issues.map((issue: any) => {
        return {
          key: issue.key,
          summary: issue.fields.summary,
          description: issue.fields.description,
        };
      });
    
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(tickets, null, 2), // Pretty print JSON
          },
        ],
      };
    }
  • Tool schema definition including name, description, and input JSON schema for JQL query and optional number of results.
    {
      name: 'get_only_ticket_name_and_description',
      description:
        'Get the name and description of the requested tickets on the api /rest/api/3/search/jql. Do not use markdown in your query.',
      inputSchema: {
        type: 'object',
        properties: {
          jql: {
            type: 'string',
            description: 'JQL query string',
          },
          number_of_results: {
            type: 'integer',
            description: 'Number of results to return',
            default: 1,
          },
        },
        required: ['jql'],
      },
    },
  • src/index.ts:61-80 (registration)
    Tool registration as part of the tools array passed to the MCP server.
    {
      name: 'get_only_ticket_name_and_description',
      description:
        'Get the name and description of the requested tickets on the api /rest/api/3/search/jql. Do not use markdown in your query.',
      inputSchema: {
        type: 'object',
        properties: {
          jql: {
            type: 'string',
            description: 'JQL query string',
          },
          number_of_results: {
            type: 'integer',
            description: 'Number of results to return',
            default: 1,
          },
        },
        required: ['jql'],
      },
    },
  • Helper function executeJQL used by the tool handler to perform the actual JQL search API call.
    async function executeJQL(jql: string, maxResults: number): Promise<any> {
      try {
        const params = {
          jql, // JQL query string
          maxResults, // Adjust as needed
          fields: '*all', // Request all fields
        };
    
        const response = await axios.get(`${JIRA_URL}/rest/api/3/search/jql`, {
          headers: getAuthHeaders().headers,
          params,
        });
    
        return response.data;
      } catch (error: any) {
        //return the error in a json
        return {
          error: error.response.data,
        };
      }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the API endpoint and a markdown restriction, but fails to disclose critical behavioral traits: whether this is a read-only operation, what permissions are needed, how errors are handled, or if there are rate limits. The markdown note is vague and doesn't clarify if it's a requirement or a warning.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief but not optimally structured. The first sentence states the purpose, but the second sentence about markdown is confusing and doesn't add clear value. It could be more front-loaded with essential information, though it avoids excessive verbosity.

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 and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., format of name and description, error responses) or behavioral constraints. For a query tool with two parameters, this leaves significant gaps in understanding how to use it effectively.

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, so the schema fully documents both parameters (jql query string and number_of_results with default). The description adds no meaningful parameter semantics beyond what's in the schema—it doesn't explain JQL syntax, valid result ranges, or how parameters interact. Baseline 3 is appropriate since the schema does the heavy lifting.

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 states the tool retrieves ticket name and description using a specific API endpoint, which provides a basic purpose. However, it doesn't clearly differentiate from sibling tools like 'execute_jql' (which likely performs similar JQL queries) or specify what makes this tool unique (e.g., limited fields returned vs. full ticket data). The mention of 'Do not use markdown in your query' is confusing and doesn't clarify the core purpose.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'execute_jql' or explain why one would choose this tool over others for querying tickets. The only usage hint is the confusing markdown restriction, which doesn't help with tool selection.

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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