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competlab

competlab-mcp-server

get_project

Retrieve project details including monitoring freshness per dimension (techTrust, content, positioning, pricing, AI visibility), AI prompts, and overall status. Use to check dimension update times before fetching data.

Instructions

Get project details including per-dimension monitoring freshness (techTrust, content, positioning, pricing, aiVisibility), AI monitoring prompts, and overall status. Use this after list_projects to check when each dimension was last updated before fetching dimension data. Read-only. Returns JSON object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID (from list_projects)

Implementation Reference

  • The ToolDef object for 'get_project' — defines the schema (projectId parameter with Zod validation) and API path (`/v1/projects/${projectId}`). This is where the tool's name, description, parameter schema, and URL path are configured.
    name: "get_project",
    description:
      "Get project details including per-dimension monitoring freshness (techTrust, content, positioning, pricing, aiVisibility), AI monitoring prompts, and overall status. Use this after list_projects to check when each dimension was last updated before fetching dimension data. Read-only. Returns JSON object.",
    parameters: z.object({
      projectId: objectId("Project ID (from list_projects)"),
    }),
    path: (a) => `/v1/projects/${a.projectId}`,
  • src/index.ts:16-25 (registration)
    Dynamic registration loop that iterates over all tools (including 'get_project') and calls `server.tool()` to register each one with the MCP server. The `tool.path(args)` is resolved and an API call is made via `apiGet`.
    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);
      });
    }
  • The `apiGet` helper function used by the tool handler. For 'get_project', it makes a GET request to `/v1/projects/{projectId}` using the COMPETLAB_API_KEY.
    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 exist, so the description carries the full burden. It declares 'Read-only' and states it returns a JSON object, covering safety and output format. It could mention error handling or authentication, but the basics are covered.

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?

Two sentences with no wasted words. The first sentence lists key fields, the second gives usage guidance and safety declaration. Excellent front-loading of critical information.

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

Completeness4/5

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

For a simple read operation with one parameter and no output schema, the description sufficiently covers what it returns, prerequisite (list_projects), and safety (read-only). Lacks explanation of return structure, but that's acceptable given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with one parameter (projectId). The description adds value by specifying 'Project ID (from list_projects)', providing source context beyond the schema's type and pattern.

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?

Clearly states it retrieves project details with specific fields like monitoring freshness, AI monitoring prompts, and overall status. The verb 'get' aligns with the tool name, and the description differentiates from sibling tools by referencing list_projects as a precursor.

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?

Explicitly advises using this after list_projects to check dimension freshness before fetching dimension data. Implicitly distinguishes from sibling tools that fetch individual dimension data. However, no explicit when-not or alternatives are provided.

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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