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fal.ai MCP Server

fal.ai MCP Server

by thenavidm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Get asset

get_asset
Read-onlyIdempotent

Fetch an asset document by vector ID from the authenticated user's fal Assets library; if the vector exists only in Turbopuffer, it returns that document with empty local state.

Instructions

Get an asset document by vector ID from the authenticated user's fal Assets library. The vector may exist only in Turbopuffer; in that case the response returns the Turbopuffer document with empty local state.

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": {
      "vector_id": "<vector_id>"
    },
    "name": "get_asset"
  }
}

Input Schema

NameRequiredDescriptionDefault
accountNoExact private account key profile label, not an authenticated provider owner ID.
vector_idYesVector ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, covering the safety profile. The description adds valuable behavioral context by noting that the vector may exist only in Turbopuffer and that the response then returns the Turbopuffer document with empty local state, which is useful edge-case disclosure beyond annotations.

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?

The description consists of two tightly written sentences with no filler. The primary purpose is front-loaded, followed by the edge-case behavior, making every sentence earn its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, 100% schema coverage, and comprehensive annotations, the description is largely complete. It adds the important Turbopuffer fallback behavior and notes the authenticated user's library, though it does not describe the general return shape beyond that edge case; with no output schema, this is a minor gap.

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 parameters (account and vector_id) are already documented in the schema. The description mentions 'by vector ID' and 'authenticated user's fal Assets library' but adds no syntax, format, or usage details beyond what the schema provides, warranting the baseline score of 3.

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 states a specific verb ('Get') and resource ('asset document by vector ID from the authenticated user's fal Assets library'), making the purpose clear. However, it does not explicitly differentiate this tool from similar siblings like list_assets or get_asset_lineage, so it falls short of a 5.

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?

The description provides no guidance on when to use this tool versus alternatives such as list_assets or search_models. It only states what the tool does, leaving the agent to infer usage conditions without any explicit when/when-not context.

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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