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Nano Banana MCP Server

by runapi-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

edit_image

Submit source images and a prompt to modify them with Nano Banana on RunAPI; returns task status and output URLs.

Instructions

Create a Nano Banana task on RunAPI (edit image). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
promptNo
timeout_msNo
aspect_ratioNo
callback_urlNo
output_formatNo
poll_interval_msNo
source_image_urlsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed14 schema fields changedv0.1.12
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / aspect_ratio / anyOf
      Added value: +[
+  {
+    "const": "1:1",
+    "type": "string"
+  },
+  {
+    "const": "1:4",
+    "type": "string"
+  },
+  {
+    "const": "1:8",
+    "type": "string"
+  },
+  {
+    "const": "2:3",
+    "type": "string"
+  },
+  {
+    "const": "3:2",
+    "type": "string"
+  },
+  {
+    "const": "3:4",
+    "type": "string"
+  },
+  {
+    "const": "4:1",
+    "type": "string"
+  },
+  {
+    "const": "4:3",
+    "type": "string"
+  },
+  {
+    "const": "4:5",
+    "type": "string"
+  },
+  {
+    "const": "5:4",
+    "type": "string"
+  },
+  {
+    "const": "8:1",
+    "type": "string"
+  },
+  {
+    "const": "9:16",
+    "type": "string"
+  },
+  {
+    "const": "16:9",
+    "type": "string"
+  },
+  {
+    "const": "21:9",
+    "type": "string"
+  },
+  {
+    "const": "auto",
+    "type": "string"
+  }
+]
    • removedInput schema / properties / aspect_ratio / enum
      Removed value: -[
-  "1:1",
-  "9:16",
-  "16:9",
-  "3:4",
-  "4:3",
-  "3:2",
-  "2:3",
-  "5:4",
-  "4:5",
-  "21:9",
-  "auto"
-]
    • removedInput schema / properties / aspect_ratio / type
      Removed value: -"string"
    • addedInput schema / properties / callback_url
      Added value: +{
+  "type": "string"
+}
    • changedInput schema / properties / model / enum
      Previous value: -[
-  "nano-banana-edit"
-]New value: +[
+  "nano-banana-2-lite",
+  "nano-banana-edit"
+]
    • addedInput schema / properties / output_format / anyOf
      Added value: +[
+  {
+    "const": "png",
+    "type": "string"
+  },
+  {
+    "const": "jpeg",
+    "type": "string"
+  }
+]
    • removedInput schema / properties / output_format / enum
      Removed value: -[
-  "png",
-  "jpeg"
-]
    • removedInput schema / properties / output_format / type
      Removed value: -"string"
    • addedInput schema / properties / poll_interval_ms / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / prompt
      Added value: +{
+  "maxLength": 20000,
+  "minLength": 1,
+  "type": "string"
+}
    • addedInput schema / properties / source_image_urls
      Added value: +{
+  "items": {},
+  "type": "array"
+}
    • addedInput schema / properties / timeout_ms / maximum
      Added value: +9007199254740991
    • addedInput schema / required
      Added value: +[
+  "source_image_urls"
+]
  2. First observedv0.1.0

TDQS

C2.4/5.0
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. It states returns (task id, status, output URLs) but doesn't disclose whether the operation is synchronous or asynchronous, how waiting works, rate limits, permissions, or side effects.

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 a single, concise sentence, but it front-loads vendor-specific jargon ('Nano Banana task on RunAPI') instead of the functional purpose. It is efficient in length but poorly prioritized.

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?

For a complex tool with 9 parameters, low schema coverage, and no annotations or output schema, the description is severely incomplete. It does not explain parameter usage, async behavior, or error handling, leaving an agent unable to invoke it reliably.

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 description coverage is only 22%, so the description must compensate. It does not mention any of the 9 parameters, failing to explain even the required source_image_urls or how wait, timeout_ms, and poll_interval_ms interact.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action (edit an image) but wraps it in vendor jargon ('Create a Nano Banana task on RunAPI') that obscures the actual purpose. It mentions returns but doesn't distinguish from sibling text_to_image.

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 guidance on when to use this tool versus text_to_image or get_task. No mention of prerequisites or alternative tools is provided.

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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