Ideogram V3 MCP Server

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.

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.

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.

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.

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.

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.

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

With no annotations, the description carries the full behavioral burden. It does add genuinely useful context by disclosing that this is an asynchronous task-creation model returning a task id and status (implying get_task follow-up), which is not derivable from the schema. However, it omits permissions, whether an edit is destructive to the source, rate limits, and how the mask constrains the operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two short sentences with zero filler, and the core action is front-loaded before the return-value clause. Every clause earns its place.

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

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

This is a 14-parameter tool with no output schema and no annotations, so the description should be doing far more work. It never explains the mask/source-image contract, the meaning of wait/poll_interval_ms, or the model/style options, leaving an agent under-informed for a fairly complex invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 86% across 14 parameters, so the schema largely documents itself and the baseline is 3. The description adds no parameter-level meaning (no explanation of mask_url, source_image_url, prompt, style, or wait semantics) beyond what the schema already states.

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

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

Names a specific verb and resource ('Create a Ideogram V3 task on RunAPI (edit image)') and states the return contract (task id, status, output URLs), so an agent knows this kicks off an image-editing job. It does not explicitly differentiate itself from the semantically nearby siblings remix_image and reframe_image, which keeps it 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.

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

There is no statement of when to choose this tool over remix_image, reframe_image, or text_to_image, and no prerequisites (e.g. that a source image and mask are mandatory) are called out. The parenthetical '(edit image)' implies the domain but gives no routing guidance.

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

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

No annotations are provided, so the description carries the full burden. It discloses what the tool returns (status plus latest result payload), which is useful, but says nothing about auth requirements, error behavior for unknown/expired task ids, or async polling semantics for a task that is not yet complete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

A single front-loaded sentence with the operation and its return payload stated up front. No filler or redundancy; every clause earns its place.

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

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

With no annotations and no output schema, the description must carry behavioral and return-value context. It names the return payload but omits polling/readiness and error-state behavior. Adequate for a simple two-parameter poll tool, but not complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and both parameters (task_id, action) are documented in the schema, including the enum values for action. The description adds no additional parameter meaning, so the baseline 3 applies.

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

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

States a specific verb (Fetch) and resource (current status and latest result payload) scoped to an 'ideogram-v3 task'. An agent can tell this is a status/result retrieval tool, distinct from the sibling creation endpoints. However, it never names or explicitly distinguishes itself from those siblings.

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

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

The description implies it is used after creating a task, but gives no explicit when-to-use guidance, no mention of polling cadence, retry, or what to do while the task is incomplete. No alternatives or exclusions are named.

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

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

With no annotations, the description carries the behavioral burden. It discloses the interactive browser flow and the file write side effect (config.json). However, it does not mention that it may overwrite existing credentials or that it could block waiting for user input, though these are implied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, well-structured sentence that front-loads the action ('Authenticate RunAPI') and provides necessary details without extraneous information.

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

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

For a simple login tool with one optional parameter and no output schema, the description covers the core purpose and side effect. It lacks an explicit statement that this is a prerequisite for other tools, but that is implied.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (the only parameter 'force' has a description). The tool description adds no additional meaning about parameters beyond the schema, so the baseline of 3 applies.

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

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

The description clearly states the tool's purpose with a specific verb ('Authenticate'), target resource ('RunAPI'), method ('browser PKCE login flow'), and side effect (saving to config.json). It is distinct from sibling tools, none of which relate to authentication.

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

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

The description implies usage (to authenticate RunAPI) but does not explicitly say when to run it (e.g., before other RunAPI tools) or when to use the 'force' parameter. Since there are no alternative auth tools among siblings, 'vs alternatives' is not applicable.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses only the return shape (task id, status, output URLs); it does not explain that the call is asynchronous, how the 'wait'/'poll_interval_ms' polling behaves, what auth is required, or what happens with callback_url.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two short sentences with the operation stated first and the return values second; no filler. Slightly dense but front-loaded and efficient.

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

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

For an 18-parameter asynchronous task tool with no annotations and no output schema, the description usefully states the return values but omits the async/polling model and any usage context. It covers the minimal essentials while leaving notable behavioral gaps for such a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 89%, so the schema already documents nearly all 18 parameters, which sets the baseline at 3. The description adds no parameter-level meaning beyond implying a source image is needed for the remix.

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

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

The description names a specific verb (Create) plus resource (Ideogram V3 task, remix image) and clarifies it acts on a source image, which hints at the distinction from text_to_image. However, it does not explain how 'remix' differs from sibling edit_image or reframe_image, so an agent cannot fully route between the image-manipulation siblings from the description alone.

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

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

There is no when-to-use or when-not-to-use guidance and no mention of the alternative image tools (edit_image, reframe_image, text_to_image). The agent is left to infer from the name which operation applies.

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

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

With no annotations, the description carries the full load. It does add real value by disclosing the async task model and the return shape (task id, status, output URLs), which no output schema supplies. However, it omits auth needs, cost/pricing implications, and how the wait/poll parameters interact with the returned task id.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two tight sentences with the action front-loaded and the return contract second. No filler, though the phrasing 'Create a Ideogram V3 task on RunAPI' is slightly awkward and the parenthetical repeats the tool name.

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

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

For a 14-parameter generation tool with no annotations and no output schema, the description is thin. It covers the return contract but says nothing about required inputs despite prompt obviously being essential, cost checks, polling via get_task, or how the wait/timeout_ms/callback_url options change behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 86%, so the schema already documents most of the 14 parameters, including enum-like known values for style, aspect_ratio, and rendering_speed. The description adds no parameter detail (e.g., model slug, output_count, callback_url) beyond that baseline.

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

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

States a specific verb (Create) plus the resource (Ideogram V3 task via RunAPI) and disambiguates with the parenthetical '(text to image)'. That distinguishes it from image-editing siblings (edit_image, reframe_image, remix_image), though it never names them directly.

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

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

There is no when-to-use guidance, no prerequisites, and no named alternative. The '(text to image)' tag hints at the domain but does not tell the agent when to pick this over remix_image or edit_image, nor that get_task/check_pricing may be needed alongside it.

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