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moliver28

anythingllm-mcp

by moliver28

check_token

Avoid authentication failures by validating the current API token before interacting with AnythingLLM workspaces and chat.

Instructions

Validate the current API token

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler for the 'system_check_token' tool. It calls the API endpoint /system/check-token via the apiRequest helper.
    else if (name === "system_check_token") { result = await apiRequest("/system/check-token"); }
  • src/index.ts:66-66 (registration)
    Registration of the 'system_check_token' tool in the ListToolsRequestSchema handler, providing its name, description, and empty input schema.
    { name: "system_check_token", description: "Check API token", inputSchema: { type: "object", properties: {}, required: [] } },
  • The apiRequest helper function that performs HTTP/HTTPS requests to the AnythingLLM API, used by the check_token handler.
    function apiRequest(path: string, method = "GET", body?: any, extraHeaders = {}): Promise<any> {
      return new Promise((resolve, reject) => {
        const baseUrl = new URL(ANYTHING_LLM_BASE);
        const fullUrl = new URL(path, baseUrl);
        const options: any = {
          hostname: fullUrl.hostname,
          port: fullUrl.port || (fullUrl.protocol === "https:" ? 443 : 80),
          path: fullUrl.pathname + fullUrl.search,
          method,
          headers: Object.assign({
            "Authorization": "Bearer " + ANYTHING_LLM_API_KEY,
            "Content-Type": "application/json",
            "Accept": "application/json",
          }, extraHeaders),
        };
    
        const lib = fullUrl.protocol === "https:" ? https : http;
        const req = lib.request(options, (res: any) => {
          let data = "";
          res.on("data", (chunk: string) => { data += chunk; });
          res.on("end", () => {
            try {
              resolve(data ? JSON.parse(data) : {});
            } catch {
              resolve({ raw: data });
            }
          });
        });
        req.on("error", reject);
        if (body) req.write(JSON.stringify(body));
        req.end();
      });
    }
Behavior2/5

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

No annotations are provided; the description merely says 'validate' without specifying outcomes, such as whether it returns a boolean or throws an error. This lacks sufficient behavioral context.

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, clear sentence with no unnecessary words. It is appropriately concise.

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

Completeness3/5

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

Given the simple nature of the tool (no parameters, no output schema), the description is minimally adequate but lacks details on validation behavior or error handling.

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?

There are zero parameters, and schema coverage is 100%. The description adds no parameter info, but baseline for no parameters is 4.

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 validates an API token, using a specific verb and resource. It distinguishes itself from sibling tools like generate_api_key or chat.

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

Usage Guidelines3/5

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

The description implies usage for checking token validity, but does not provide explicit when-to-use or when-not-to-use guidance compared to alternatives.

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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