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wenkezhi8

2Xapi.com GPT-image MCP Server

by wenkezhi8

Update GPT-image config

set_config

Configure GPT-image generation by updating API base URL, key, model, size, or save directory. Changes persist to config and take effect immediately for next image generation.

Instructions

Update one or more GPT-image settings and persist them to the config file. Any field left null/omitted is unchanged. Changes take effect immediately for subsequent generate_image calls — no restart needed. Fields: api_base_url, api_key, model, size, save_dir.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNo
modelNo
api_keyNo
save_dirNo
api_base_urlNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explains persistence to a config file, that null/omitted fields remain unchanged, and that changes apply immediately without restart. This is valuable behavioral insight beyond a basic 'update' statement, though it does not cover potential validation 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.

Conciseness5/5

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

The description is three sentences: purpose, behavior, and field list. It is front-loaded and each sentence earns its place. No filler or repetition of schema information.

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?

For a config-update tool with no annotations and 5 parameters, the description covers the key aspects: partial update semantics, persistence, immediate effect, and the relevant fields. An output schema exists, so not explaining the return value is acceptable. It could have added a note about validation or file location, but overall it is complete enough.

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 0%, so the description must compensate. It lists all five field names and explains the null/omitted behavior, which adds meaning beyond the raw schema. However, it does not elaborate on the role or allowed values of each field, relying on the self-explanatory names.

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 'Update one or more GPT-image settings and persist them to the config file,' which is a specific verb + resource. It also lists the exact fields involved, making it easy to distinguish from sibling tools like get_config (read) and generate_image (use).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context by noting that changes take effect immediately for subsequent generate_image calls, implying this is the tool to use before generating images. It does not explicitly name alternatives or exclusions, but the intended usage is clear from the 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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