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retell_get_llm

Retrieve a specific LLM configuration from Retell AI's voice and chat agent platform to manage conversation flows and agent behavior.

Instructions

Retrieve a Retell LLM configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
llm_idYesThe LLM configuration ID

Implementation Reference

  • Handler case in executeTool function that performs a GET request to the Retell API endpoint /get-retell-llm/{llm_id} using the generic retellRequest helper.
    case "retell_get_llm":
      return retellRequest(`/get-retell-llm/${args.llm_id}`, "GET");
  • Input schema definition for the retell_get_llm tool, requiring llm_id parameter.
    {
      name: "retell_get_llm",
      description: "Retrieve a Retell LLM configuration.",
      inputSchema: {
        type: "object",
        properties: {
          llm_id: {
            type: "string",
            description: "The LLM configuration ID"
          }
        },
        required: ["llm_id"]
      }
    },
  • Generic helper function for making authenticated HTTP requests to the Retell AI API, used by the retell_get_llm handler.
    async function retellRequest(
      endpoint: string,
      method: string = "GET",
      body?: Record<string, unknown>
    ): Promise<unknown> {
      const apiKey = getApiKey();
    
      const headers: Record<string, string> = {
        "Authorization": `Bearer ${apiKey}`,
        "Content-Type": "application/json",
      };
    
      const options: RequestInit = {
        method,
        headers,
      };
    
      if (body && method !== "GET") {
        options.body = JSON.stringify(body);
      }
    
      const response = await fetch(`${RETELL_API_BASE}${endpoint}`, options);
    
      if (!response.ok) {
        const errorText = await response.text();
        throw new Error(`Retell API error (${response.status}): ${errorText}`);
      }
    
      // Handle 204 No Content
      if (response.status === 204) {
        return { success: true };
      }
    
      return response.json();
    }
  • src/index.ts:1283-1285 (registration)
    Registration of the tool list handler that exposes the retell_get_llm tool (included in the tools array) via MCP protocol.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return { tools };
    });
  • Helper function to retrieve the Retell API key from environment variable, used by retellRequest.
    function getApiKey(): string {
      const apiKey = process.env.RETELL_API_KEY;
      if (!apiKey) {
        throw new Error("RETELL_API_KEY environment variable is required");
      }
      return apiKey;
    }
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It doesn't disclose whether this is a read-only operation, what permissions are required, error handling (e.g., invalid IDs), or response format. For a retrieval tool with zero annotation coverage, this is a significant gap in transparency.

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 that front-loads the core purpose without unnecessary words. It avoids redundancy and wastes no space, making it easy for an agent 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 lack of annotations and output schema, the description is incomplete for a retrieval tool. It doesn't explain what data is returned (e.g., configuration details, status) or behavioral aspects like error cases. With 100% schema coverage, the input is well-documented, but overall context remains insufficient for confident tool invocation.

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?

The input schema has 100% description coverage, with 'llm_id' clearly documented as 'The LLM configuration ID'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. This meets the baseline score of 3 when schema coverage is high.

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 ('Retrieve') and resource ('Retell LLM configuration'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'retell_create_llm' and 'retell_update_llm' by focusing on retrieval rather than creation or modification. However, it doesn't specify the scope (e.g., all fields or specific metadata), which prevents a perfect score.

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 on when to use this tool versus alternatives. While the description implies it's for retrieving existing configurations, it doesn't mention prerequisites (e.g., needing a valid LLM ID) or contrast with similar tools like 'retell_list_llms' for listing all configurations. This leaves the agent without explicit usage context.

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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