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callremind

CallRemind MCP Server

Official
by callremind

createAgent

Create an AI agent for call reminders by setting its name, voice, and first spoken line. Configure the agent to make instant calls and manage notifications.

Instructions

Create an AI agent. Required: name, voice, agent_start_message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoSystem prompt / instructions
nameYesAgent name
voiceNoOpenAI voice (alloy, sage, ...)
owner_emailNoIgnored for user API keys; required only with system API key
agent_start_messageNoFirst spoken line

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.6

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description bears the full burden of behavioral disclosure, but only says 'Create an AI agent.' It does not mention side effects, permissions, idempotency, or what the response contains. It also contradicts the input schema by claiming voice and agent_start_message are required when only name is required.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, which is structurally good. However, the 'Required' phrase is inaccurate and does not truly earn its place because it misrepresents the schema and could cause incorrect agent behavior.

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?

This is a creation tool with no output schema, no annotations, and a misleading required-fields note. An agent lacks information about what happens after creation, how the response is structured, and which fields are genuinely optional. It is not complete enough for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds no useful parameter meaning and actively misleads by asserting fields are required that the schema does not require. This makes the description worse than simply relying on the schema.

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 action ('Create') and the resource ('an AI agent'), which is a specific verb+resource pair. It is reasonably distinguishable from sibling tools like updateAgent and listAgents, though the description alone does not emphasize the distinction.

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 guidance on when to use this tool versus alternatives such as createVoiceClone or updateAgent. The 'Required' note is about fields, not usage context, and provides no exclusions or decision criteria.

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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