Skip to main content
Glama
runapi-ai

Ideogram V3 MCP Server

by runapi-ai

check_pricing

Look up RunAPI pricing for Ideogram V3 text-to-image, edit, and remix actions, with defaults when model or endpoint is omitted.

Instructions

Look up RunAPI pricing for the ideogram-v3 model line.

Input Schema

NameRequiredDescriptionDefault
modelNoModel slug. Defaults to the line's primary model.
actionNoEndpoint name. Defaults to the endpoint that offers the model.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.0
    • changedInput schema / properties / action / enum
      Previous value: -[
      -  "edit_image",
      -  "reframe_image",
      -  "remix_image",
      -  "text_to_image"
      -]New value: +[
      +  "edit_image",
      +  "remix_image",
      +  "text_to_image"
      +]
  2. Changed2 schema fields changedv0.2.0
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / model / enum
      Removed value: -[
      -  "ideogram-v3-character-edit",
      -  "ideogram-v3-edit",
      -  "ideogram-v3-reframe",
      -  "ideogram-v3-character-remix",
      -  "ideogram-v3-remix",
      -  "ideogram-v3-character",
      -  "ideogram-v3-text-to-image"
      -]
  3. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. 'Look up' implies a non-mutating read, which is useful, but it does not disclose the pricing shape (per-call vs per-token, currency), whether results are static or live, or rate limits for a tool with no output schema.

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 naming verb, resource, and scope with zero filler. Every word earns its place.

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?

The tool is simple and both parameters are fully documented in the schema, but because there is no output schema, the description should have clarified the return format for pricing. The hardcoded 'ideogram-v3' also sits slightly awkwardly against the generic model parameter, which accepts other models.

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%, so both the model slug and action enum are already documented. The description adds only the 'ideogram-v3 model line' context, and it does not explain how the model/action interact or what defaults resolve to beyond what the schema states.

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?

States a specific verb (look up) and resource (RunAPI pricing) scoped to the ideogram-v3 model line. It is easily distinguishable from siblings like edit_image and text_to_image, which are action tools, though it does not explicitly name or contrast with them.

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?

No when-to-use, when-not, or alternatives are provided. Usage (presumably checking cost before making calls) is only implied by the verb 'look up', leaving the agent to infer context.

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