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retell_get_chat_agent

Retrieve details of a specific chat agent to manage conversation flows and configure AI interactions for voice and chat platforms.

Instructions

Retrieve details of a specific chat agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesThe chat agent ID

Implementation Reference

  • Handler logic for retell_get_chat_agent tool: makes a GET request to Retell API endpoint `/get-chat-agent/${agent_id}` using the retellRequest helper.
    case "retell_get_chat_agent":
      return retellRequest(`/get-chat-agent/${args.agent_id}`, "GET");
  • Tool definition including name, description, and input schema (requires agent_id string). This is part of the tools array used for MCP tool listing.
    {
      name: "retell_get_chat_agent",
      description: "Retrieve details of a specific chat agent.",
      inputSchema: {
        type: "object",
        properties: {
          agent_id: {
            type: "string",
            description: "The chat agent ID"
          }
        },
        required: ["agent_id"]
      }
    },
  • src/index.ts:1283-1285 (registration)
    MCP server handler for listing tools, which returns the tools array containing the retell_get_chat_agent definition.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return { tools };
    });
  • Generic helper function for making authenticated HTTP requests to the Retell AI API, used by the tool 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();
    }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It doesn't indicate whether this is a read-only operation, what authentication is required, whether rate limits apply, what format the returned details follow, or if there are any side effects. For a retrieval tool with zero annotation coverage, this represents a significant transparency gap.

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 perfectly concise at just one sentence that directly states the tool's purpose. There's zero wasted language, no redundancy, and the information is front-loaded effectively. Every word earns its place in this minimal but complete statement of function.

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?

For a simple retrieval tool with one parameter and no output schema, the description provides the basic purpose but lacks important context. Without annotations or output schema, the agent doesn't know what details are returned, in what format, or under what conditions. The description is adequate for the simplest case but doesn't prepare the agent for potential complexities or edge cases.

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 the single parameter 'agent_id' clearly documented as 'The chat agent ID'. The description doesn't add any meaningful semantic information beyond what the schema already provides, such as format examples, validation rules, or relationship to other identifiers. With complete schema coverage, the baseline score of 3 is appropriate.

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 details') and resource ('specific chat agent'), making the purpose immediately understandable. However, it doesn't differentiate this tool from similar sibling tools like 'retell_get_agent' or 'retell_list_chat_agents', which would require more specificity about what distinguishes this particular retrieval operation.

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 about when to use this tool versus alternatives. With sibling tools like 'retell_get_agent', 'retell_list_chat_agents', and 'retell_get_chat' available, the agent receives no indication about whether this is for single-agent lookup, bulk retrieval, or chat-specific agent details. The description lacks any contextual usage information.

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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