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Plane MCP Server

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by makeplane

get_issue_worklogs

Retrieve all worklogs associated with a specific issue in a project using the Plane MCP Server, facilitating detailed tracking and management of task progress.

Instructions

Get all worklogs for a specific issue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_idYesThe uuid identifier of the issue to get worklogs for
project_idYesThe uuid identifier of the project containing the issue

Implementation Reference

  • The core handler function that fetches worklogs via a GET request to the Plane API for the specified project and issue, returning the JSON response as MCP text content.
    async ({ project_id, issue_id }) => {
      const response = await makePlaneRequest(
        "GET",
        `workspaces/${process.env.PLANE_WORKSPACE_SLUG}/projects/${project_id}/issues/${issue_id}/worklogs/`
      );
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(response, null, 2),
          },
        ],
      };
    }
  • Input schema defined using Zod, requiring project_id and issue_id as strings.
    {
      project_id: z.string().describe("The uuid identifier of the project containing the issue"),
      issue_id: z.string().describe("The uuid identifier of the issue to get worklogs for"),
    },
  • Direct registration of the get_issue_worklogs tool on the MCP server within the registerWorkLogTools function, including name, description, input schema, and inline handler.
    server.tool(
      "get_issue_worklogs",
      "Get all worklogs for a specific issue",
      {
        project_id: z.string().describe("The uuid identifier of the project containing the issue"),
        issue_id: z.string().describe("The uuid identifier of the issue to get worklogs for"),
      },
      async ({ project_id, issue_id }) => {
        const response = await makePlaneRequest(
          "GET",
          `workspaces/${process.env.PLANE_WORKSPACE_SLUG}/projects/${project_id}/issues/${issue_id}/worklogs/`
        );
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(response, null, 2),
            },
          ],
        };
      }
    );
  • Utility function called by the handler to perform authenticated HTTP requests to the Plane API using axios.
    export async function makePlaneRequest<T>(method: string, path: string, body: any = null): Promise<T> {
      const hostUrl = process.env.PLANE_API_HOST_URL || "https://api.plane.so/";
      const host = hostUrl.endsWith("/") ? hostUrl : `${hostUrl}/`;
      const url = `${host}api/v1/${path}`;
      const headers: Record<string, string> = {
        "X-API-Key": process.env.PLANE_API_KEY || "",
      };
    
      // Only add Content-Type for non-GET requests
      if (method.toUpperCase() !== "GET") {
        headers["Content-Type"] = "application/json";
      }
    
      try {
        const config: AxiosRequestConfig = {
          url,
          method,
          headers,
        };
    
        // Only include body for non-GET requests
        if (method.toUpperCase() !== "GET" && body !== null) {
          config.data = body;
        }
    
        const response = await axios(config);
        return response.data;
      } catch (error) {
        if (axios.isAxiosError(error)) {
          throw new Error(`Request failed: ${error.message}`);
        }
        throw error;
      }
    }
  • Invocation of registerWorkLogTools in the central tools registration function, which includes the get_issue_worklogs tool.
    registerWorkLogTools(server);
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 a read operation ('Get') but doesn't cover aspects like authentication needs, rate limits, pagination, or response format. This is inadequate for a tool with potential complexity in data retrieval.

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, efficient sentence with zero waste—it directly states the tool's function without unnecessary details. It's appropriately sized and front-loaded for quick understanding.

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 'worklogs' entail, how results are returned, or any behavioral traits, making it insufficient for an agent to use the tool effectively in a complex environment.

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 (issue_id and project_id). The description adds no additional meaning beyond implying these are required for fetching worklogs, 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 ('Get') and resource ('all worklogs for a specific issue'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_total_worklogs' or 'get_issue_comments', which could cause confusion in selection.

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, such as 'get_total_worklogs' for aggregated data or 'get_issue_comments' for related issue details. It lacks context on prerequisites or exclusions, leaving usage ambiguous.

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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