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retell_list_conversation_flows

Retrieve and view all conversation flows configured in the Retell AI platform for managing voice and chat agents.

Instructions

List all conversation flows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Switch case in the executeTool function that handles execution of retell_list_conversation_flows by calling the Retell API endpoint /list-conversation-flows via GET request.
    case "retell_list_conversation_flows":
      return retellRequest("/list-conversation-flows", "GET");
  • Tool schema definition specifying the name, description, and empty input schema for the retell_list_conversation_flows tool.
    {
      name: "retell_list_conversation_flows",
      description: "List all conversation flows.",
      inputSchema: {
        type: "object",
        properties: {}
      }
    },
  • src/index.ts:1283-1285 (registration)
    MCP server request handler for listing tools, which returns the tools array containing the schema for retell_list_conversation_flows.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return { tools };
    });
  • Generic retellRequest helper function that makes authenticated HTTP requests to the Retell API, used by the tool handler to fetch the list of conversation flows.
    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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List all conversation flows' implies a read-only operation, but it doesn't specify whether this requires authentication, returns paginated results, includes metadata, or has rate limits. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 with zero wasted words. It's front-loaded with the core action ('List all conversation flows') and doesn't include unnecessary details. Every word earns its place, 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.

Completeness3/5

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

Given the tool's simplicity (0 parameters, no output schema), the description is minimally adequate. It states what the tool does but lacks context about the return format, authentication needs, or error handling. Without annotations or output schema, the agent must assume basic list behavior, which is sufficient but not complete.

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?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter information, and it correctly implies no filtering or arguments are required. A baseline of 4 is appropriate for parameterless tools when the schema is complete.

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 ('List') and resource ('all conversation flows'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'retell_get_conversation_flow' (singular retrieval) by indicating it returns multiple items. However, it doesn't specify the scope or format of the listing, 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for listing flows, or differentiate from similar list tools like 'retell_list_agents' or 'retell_list_calls'. Without any usage instructions, the agent must infer context from the tool name alone.

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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