@monsoft/mcp-fal-ai

fal-run-sync

Execute AI models synchronously and automatically convert image URLs to base64 data in the response for direct use.

Instructions

Run a model synchronously and automatically download any image URLs in the response. The model is run synchronously using the fal.run endpoint. Returns the model output with embedded base64 image data for any image URLs found.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "modelId": "<modelId>"
    },
    "name": "fal-run-sync"
  }
}

Input Schema

Name	Required	Description	Default
`modelId`	Yes
`input`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Apr 28, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Discloses synchronous execution, automatic image URL download, and base64 embedding. Missing details on failure handling or side effects, but provides key behavioral traits beyond the 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?

Three sentences, front-loaded with the primary action, each sentence contributes unique value without redundancy.

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?

Missing parameter descriptions and usage context. Despite explaining the return format, the lack of parameter guidance makes it incomplete for correct 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 0% with no parameter descriptions. The tool description adds no meaning to modelId or input parameters, leaving the agent without guidance.

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

Purpose5/5

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

The description clearly states the tool runs a model synchronously and automatically processes image URLs, distinguishing it from async alternatives like fal-enqueue.

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 explicit guidance on when to use this tool vs siblings like fal-enqueue or fal-get-result. The description does not mention when not to use it.

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

Deploy Server