Skip to main content
Glama
competlab

competlab-mcp-server

list_schedules

Retrieve monitoring schedules for all five dimensions including status, interval in days, next and last run timestamps. Use to check upcoming monitoring runs or verify schedule configuration.

Instructions

Get monitoring schedules for all 5 dimensions. Returns enabled/disabled status, interval in days, next run timestamp, and last run timestamp per dimension. Dimension names use marketing names (tech-trust, content, positioning, pricing, ai-visibility). Use this to check when the next monitoring run is due or verify scheduling configuration. Read-only. Returns JSON array.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID (from list_projects)

Implementation Reference

  • ToolDef interface defines the shape of each tool: name, description, parameters (Zod schema), path (URL builder), and optional queryParams. This is the type used for all tool definitions including list_schedules.
    export interface ToolDef {
      name: string;
      description: string;
      parameters: z.ZodObject<any>;
      path: (args: Record<string, any>) => string;
      queryParams?: string[];
    }
  • Schema definition for the list_schedules tool. Defines the tool's name, description, Zod-validated parameters (projectId as 24-char hex string), and path builder that maps to GET /v1/projects/{projectId}/schedules.
    {
      name: "list_schedules",
      description:
        "Get monitoring schedules for all 5 dimensions. Returns enabled/disabled status, interval in days, next run timestamp, and last run timestamp per dimension. Dimension names use marketing names (tech-trust, content, positioning, pricing, ai-visibility). Use this to check when the next monitoring run is due or verify scheduling configuration. Read-only. Returns JSON array.",
      parameters: z.object({
        projectId: objectId("Project ID (from list_projects)"),
      }),
      path: (a) => `/v1/projects/${a.projectId}/schedules`,
    },
  • src/index.ts:16-25 (registration)
    Registration loop: list_schedules is registered with the MCP server via server.tool(...) by iterating the tools array. The handler is a generic async function that calls apiGet with the tool's path and optional query params.
    for (const tool of tools) {
      server.tool(tool.name, tool.description, tool.parameters.shape, async (args: Record<string, any>) => {
        const path = tool.path(args);
        const query: Record<string, any> = {};
        for (const key of tool.queryParams ?? []) {
          if (args[key] !== undefined) query[key] = args[key];
        }
        return apiGet(path, Object.keys(query).length ? query : undefined);
      });
    }
  • apiGet is the actual HTTP execution handler. It constructs the URL from the base (https://api.competlab.com) + path (e.g., /v1/projects/{id}/schedules), adds query parameters, sets the CL-API-Key header, fetches the data, and returns the response text as MCP content.
    export async function apiGet(
      path: string,
      query?: Record<string, string | number>,
    ): Promise<{ content: Array<{ type: "text"; text: string }>; isError?: true }> {
      const apiKey = process.env.COMPETLAB_API_KEY;
      if (!apiKey) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                error: "api_key_missing",
                message: "COMPETLAB_API_KEY environment variable is not set",
              }),
            },
          ],
          isError: true,
        };
      }
    
      const url = new URL(`${API_BASE}${path}`);
      if (query) {
        for (const [k, v] of Object.entries(query)) {
          if (v !== undefined) url.searchParams.set(k, String(v));
        }
      }
    
      try {
        const res = await fetch(url, {
          headers: { "CL-API-Key": apiKey },
        });
    
        const body = await res.text();
    
        if (!res.ok) {
          return { content: [{ type: "text", text: body }], isError: true };
        }
    
        return { content: [{ type: "text", text: body }] };
      } catch (err) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                error: "api_unreachable",
                message:
                  err instanceof Error ? err.message : "Failed to reach CompetLab API",
                status: 503,
              }),
            },
          ],
          isError: true,
        };
      }
    }
Behavior4/5

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

No annotations provided, so description carries full burden. It states 'Read-only' and 'Returns JSON array,' disclosing key behavioral traits. No contradictions.

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?

Three sentences, front-loaded with core purpose, then specific fields and dimension names. No unnecessary words or repetition. Efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with one required parameter and no output schema, the description fully covers what is returned, how to use it, and the dimension naming. Complete.

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?

Input schema has 100% coverage for the single parameter (projectId) with a pattern and description. Description adds no additional parameter meaning beyond what schema provides, so baseline score of 3 applies.

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

Purpose5/5

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

The description clearly states the tool retrieves monitoring schedules for all 5 dimensions, listing specific fields and dimension names. It distinguishes from sibling tools which are mostly per-dimension dashboards or history.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this to check when the next monitoring run is due or verify scheduling configuration,' providing clear usage context. It does not mention when not to use or alternatives, but given sibling tools, this is clear enough.

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/competlab/competlab-mcp-server'

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