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Vapi MCP Server

Vapi MCP Server

Official
by VapiAI

create_simulation_personality

Creates a simulated caller personality for testing Vapi assistants, letting you define the caller that interacts with the assistant under test.

Instructions

Creates a simulation personality: the simulated caller that talks to the assistant under test

Input Schema

NameRequiredDescriptionDefault
nameYesThis is the name of the personality (e.g., "Confused Carl", "Rude Rob").
pathNoOptional folder path for organizing personalities. Supports up to 3 levels (e.g., "dept/feature/variant"). Maps to GitOps resource folder structure.
assistantYesFull tester assistant configuration, validated against the bundled Vapi OpenAPI schema. See https://api.vapi.ai/api-json (TransientAssistantDTO).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.0

TDQS

C2.9/5.0
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 behavioral burden. It says nothing beyond the bare fact of creation: no word on name-collision behavior, whether the referenced assistant must already exist, required permissions, or what the call returns.

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?

A single front-loaded sentence with zero padding; the definition of the resource follows immediately after the verb. Nothing here is wasted or restated from the schema.

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?

The tool takes a nested, additionalProperties-open assistant DTO validated against an external Vapi schema, has no annotations, and no output schema. For that complexity the description is thin: it never hints that the assistant argument is a full transient-assistant configuration, nor what a successful call produces or how the personality relates to a later simulation run.

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?

Schema description coverage is 100%, with name, path, and the nested assistant object all documented in the schema, so the baseline is 3. The description adds no parameter-level meaning beyond identifying that the personality acts as a simulated caller, which is contextual rather than semantic detail about the arguments.

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 uses a specific verb plus resource ("Creates a simulation personality") and then defines the concept inline as "the simulated caller that talks to the assistant under test," which an agent could not infer from the name alone. It stops short of differentiating this from close siblings such as create_simulation_scenario or create_simulation, so it is clear but not sibling-aware.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. Given siblings like create_simulation_scenario and create_simulation, an agent gets no help deciding which creation tool to call when setting up a test.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.