Skip to main content
Glama
ratheesh-aot

Clockify MCP Server

by ratheesh-aot

update_tag

Modify existing tags in Clockify workspaces to update names or archive status for better time tracking organization.

Instructions

Update an existing tag

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdYesWorkspace ID
tagIdYesTag ID
nameNoTag name
archivedNoWhether tag is archived

Implementation Reference

  • Executes the update_tag tool by sending a PUT request to the Clockify API to update the specified tag with the provided data (name, archived status). Returns a success message with updated tag info.
    private async updateTag(args: any) {
      const { workspaceId, tagId, ...updateData } = args;
    
      const tag = await this.makeRequest(
        `/workspaces/${workspaceId}/tags/${tagId}`,
        "PUT",
        updateData
      );
    
      return {
        content: [
          {
            type: "text",
            text: `Tag updated successfully!\nName: ${tag.name}\nArchived: ${tag.archived}`,
          },
        ],
        isError: false,
      };
    }
  • Input schema defining parameters for the update_tag tool: requires workspaceId and tagId, optional name and archived.
    inputSchema: {
      type: "object",
      properties: {
        workspaceId: { type: "string", description: "Workspace ID" },
        tagId: { type: "string", description: "Tag ID" },
        name: { type: "string", description: "Tag name" },
        archived: { type: "boolean", description: "Whether tag is archived" },
      },
      required: ["workspaceId", "tagId"],
    },
  • src/index.ts:636-648 (registration)
    Tool registration in the list of available tools returned by ListToolsRequest, including name, description, and input schema.
      name: "update_tag",
      description: "Update an existing tag",
      inputSchema: {
        type: "object",
        properties: {
          workspaceId: { type: "string", description: "Workspace ID" },
          tagId: { type: "string", description: "Tag ID" },
          name: { type: "string", description: "Tag name" },
          archived: { type: "boolean", description: "Whether tag is archived" },
        },
        required: ["workspaceId", "tagId"],
      },
    },
  • src/index.ts:805-807 (registration)
    Dispatch handler in the CallToolRequest switch statement that validates inputs and calls the updateTag method.
    case "update_tag":
      if (!args?.workspaceId || !args?.tagId) throw new McpError(ErrorCode.InvalidParams, 'workspaceId and tagId are required');
      return await this.updateTag(args as any);
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 of behavioral disclosure. 'Update an existing tag' implies a mutation operation, but it doesn't disclose any behavioral traits such as required permissions, whether changes are reversible, rate limits, error conditions, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.

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—'Update an existing tag' is front-loaded and appropriately sized for the tool's purpose. Every word earns its place, 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 mutation with 4 parameters, no annotations, and no output schema), the description is incomplete. It lacks information on behavioral aspects, usage context, and expected outcomes. For a tool that modifies data, more detail is needed to ensure safe and correct use by an AI agent.

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 already documents all four parameters (workspaceId, tagId, name, archived) with clear descriptions. The description adds no meaning beyond what the schema provides—it doesn't explain parameter interactions, defaults, or examples. Baseline 3 is appropriate when 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 'Update an existing tag' clearly states the action (update) and resource (tag), but it's vague about what specifically gets updated. It distinguishes from sibling tools like 'create_tag' and 'delete_tag' by specifying 'existing', but doesn't differentiate from other update tools (e.g., update_client, update_project) beyond the resource type.

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing workspaceId and tagId), when not to use it (e.g., for creating new tags), or how it relates to sibling tools like 'get_tags' for retrieving tags first. Usage is implied by the name but not explicitly stated.

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/ratheesh-aot/clockify-mcp'

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