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retell_get_agent

Retrieve configuration and details for a specific voice agent to manage conversation flows and agent settings.

Instructions

Retrieve the configuration and details of a specific voice agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesThe unique identifier of the agent

Implementation Reference

  • The handler logic for the 'retell_get_agent' tool within the executeTool switch statement. It constructs the API endpoint using the agent_id from input args and calls the retellRequest helper.
    case "retell_get_agent":
      return retellRequest(`/get-agent/${args.agent_id}`, "GET");
  • The tool schema definition including name, description, and inputSchema for validating the agent_id parameter.
    {
      name: "retell_get_agent",
      description: "Retrieve the configuration and details of a specific voice agent.",
      inputSchema: {
        type: "object",
        properties: {
          agent_id: {
            type: "string",
            description: "The unique identifier of the agent"
          }
        },
        required: ["agent_id"]
      }
    },
  • src/index.ts:1283-1285 (registration)
    Registration of the tool listing handler that exposes all tools, including 'retell_get_agent', via the MCP protocol.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return { tools };
    });
  • Core HTTP client helper function that performs authenticated API requests to Retell AI backend, used by all tool handlers including retell_get_agent.
    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:1288-1293 (registration)
    MCP server request handler for tool execution, which dispatches to executeTool based on tool name, enabling 'retell_get_agent' execution.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      const { name, arguments: args } = request.params;
    
      try {
        const result = await executeTool(name, args as Record<string, unknown>);
        return {
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 it 'retrieves' details without disclosing behavioral traits. It doesn't mention whether this is a read-only operation, requires authentication, has rate limits, returns structured data, or handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action ('retrieve') and resource, 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 lack of annotations and output schema, the description is incomplete for a retrieval tool. It doesn't explain what 'configuration and details' includes, the return format, or error handling. While the schema covers the input well, the overall context for proper tool invocation remains insufficient.

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 description adds no parameter semantics beyond what the schema provides, which has 100% coverage with a clear description for 'agent_id'. The baseline score of 3 is appropriate since the schema fully documents the single required parameter, and the description doesn't need to compensate for gaps.

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 verb 'retrieve' and the resource 'configuration and details of a specific voice agent', making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'retell_get_agent_versions' or 'retell_list_agents', which also retrieve agent information but with different scopes.

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?

The description provides no guidance on when to use this tool versus alternatives like 'retell_list_agents' (for listing multiple agents) or 'retell_get_agent_versions' (for version-specific details). It mentions 'specific voice agent' but doesn't clarify prerequisites or exclusions, leaving the agent to infer 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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