MCP tools for single and multi-prompt agents

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When to use MCP tools

• You already run an MCP server — reuse the same tools your other AI agents and IDE assistants call, without rebuilding them as custom functions.
• You want many tools from one integration — connect once, then pick which of the server’s tools the agent can access, instead of configuring each endpoint separately.
• You use a third-party MCP server — connect to a hosted MCP service (search, CRM, internal tooling) that already speaks the protocol.

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Example: order lookup over MCP

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How it works

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Connect an MCP server

1

Add the MCP server

In your agent, open the MCPs section and click Add MCP.

In the dialog, enter a name for the server and its URL. The URL field is masked by default; use the reveal icon to check it.

2

Set request headers (optional)

Under Headers, add the key/value pairs Retell sends with the MCP connection request — most often an auth header such as Authorization: Bearer <token>. Click New key value pair for each header. Values can include dynamic variables, so you can pass a per-call token as {{api_key}}.

3

Set query parameters (optional)

Under Query Parameters, add key/value pairs Retell appends to the server URL as a query string. Use this for servers that authenticate or route by query parameter. Values can include dynamic variables too.

4

Save the server

Click Save. The server appears in the MCPs section, ready for you to add tools.

5

Add a tool

On the saved server, click Add Tools. In Tool Access Scope, open the Select Tool dropdown and pick a tool — Retell connects to the server and lists its tools, each with its name and description.

Add a tool for each of the server’s tools you want the agent to be able to call. Only the tools you add here are exposed to the agent.

6

Set response variables (optional)

In Store Fields as Variables, extract values from the tool’s response and save them as dynamic variables to use later in the call. Each row maps a variable name to the path of a field in the response, using dot notation with array indexing where needed — for example user.name or data.items[0].id. This works only when the tool returns a JSON object.For example, from this response you could save the name and reference it later as {{user_name}}:

{
  "user": {
    "name": "John Doe",
    "age": 26
  }
}

7

Configure speech behavior

Control what the agent does while the tool runs and after it returns:

• Talk While Waiting (off by default) — the agent says a short line to fill the silence while the tool runs, like “Let me look that up for you.” Choose Prompt to have the LLM generate the line, or Static Sentence to speak a fixed message you write. Turn it on for user-facing lookups; leave it off for background tasks. You can also enable Play typing sound to play a subtle typing sound while the tool runs.
• Talk After Action Completed (on by default) — the agent responds again once the tool returns, so it can read back the result or call another tool. Turn it off only for fire-and-forget tasks, like silently uploading a result to your server.

8

Save the tool

Click Save. The tool now appears under the server in the MCPs section.

9

Tell the agent when to call the tool

In your prompt, say explicitly when the agent should call each tool — the agent decides from the tool’s name, description, and your prompt. For example:

When the user gives their name and phone number, call the `verify_user` tool.

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FAQ