RunAPI Midjourney MCP Server

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, yet it says nothing about whether this is a safe read-only call, whether it hits a live API or cached data, or what the response contains. Since no output schema exists either, the description should have filled this gap and does not.

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 no wasted words, appropriate for a simple lookup tool. It is efficient, though its brevity is partly the source of the missing behavioral and usage detail.

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 output schema, the description is the only place an agent could learn what pricing information comes back (per-call cost, credits, currency, model/action granularity), and it omits all of that. It also fails to disambiguate the midjourney-plus-video-action scope mismatch against the video siblings.

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 parameters (model and action) are already documented in the schema, establishing a baseline of 3. The description adds only the 'midjourney model line' scope hint, which loosely connects to the model parameter but provides no syntax or default-behavior detail beyond the schema.

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 and resource ("look up RunAPI pricing") and scopes it to the midjourney model line, which distinguishes it from the sibling action endpoints like edit_image and get_seed. It is clear what the tool does, though it does not explicitly name which sibling it substitutes for.

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 gives no when-to-use or when-not-to-use guidance; it never says when an agent should call this versus executing one of the sibling action endpoints. Only the implied 'need a price, look it up' reading provides any direction.

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 does disclose the async task model and the return shape (task id, status, output URLs), which is genuinely useful, but it omits whether the operation is billed, what permissions/auth are required, and how the wait/polling workflow behaves.

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 no filler. It is efficient, though the parenthetical '(edit image)' is a slightly thin substitute for real scoping 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?

The description compensates for the missing output schema by summarizing return values, which is a real contribution. However, for a 9-parameter async task tool with no annotations, the absence of usage routing and parameter meaning leaves meaningful gaps.

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 coverage is 78%, near the baseline-3 threshold, but the description adds nothing about any parameter. Critically, the required prompt and source_image_url are documented only as 'Declared type: string', and mask_url — central to an image-editing tool — is never explained in either the schema or the description.

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) and resource (Midjourney task on RunAPI) and qualifies it with '(edit image)', which separates it from text_to_image and image_to_video. It stops short of explicitly differentiating from the other image siblings, but the core purpose is unambiguous.

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 and no mention of alternatives such as text_to_image (no source image) or image_to_video (video output). An agent must infer the selection criteria purely from the tool name.

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 usefully discloses that this is an async remote task submission that returns a task id, status, and output URLs, but it says nothing about side effects, cost/pricing implications, auth requirements, or how the wait/polling parameters change behavior.

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, front-loaded with the action and provider, then the return shape. Nothing is padded, though the parenthetical '(extend video)' is slightly redundant with 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?

With no output schema, the mention of returned task id/status/output URLs is genuinely valuable, but for a task-creation tool exposing polling controls and a callback URL, the description should say more about async behavior and the wait/poll contract. It is minimally adequate rather than 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?

Seven parameters, and the schema's own descriptions are thin — several are just 'Declared type: string' and timeout_ms/poll_interval_ms have none at all. The description adds no meaning for wait, timeout_ms, poll_interval_ms, callback_url, or model, so it fails to compensate for the real coverage gap (only 2 of 7 params carry genuine descriptions).

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 a task) and the operation's resource (extend video) on a named provider (Midjourney via RunAPI), which lets an agent distinguish it from siblings like image_to_video or text_to_image. It stops short of explicitly differentiating itself from those siblings, so it is clear but not routing-grade.

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 use this tool versus alternatives such as image_to_video or edit_image, and no prerequisites (e.g. that source_task_id must reference an existing video task). The name and parenthetical imply the scenario, but usage is left entirely to inference.

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 discloses that the call is synchronous and returns the operation result, which is useful against async siblings, but says nothing about auth requirements, cost/pricing implications, failure modes, or what 'the operation result' actually contains.

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, front-loaded with the operation type. The second sentence ('Returns the operation result') is nearly filler but the overall size is appropriate and wastes little space.

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 single-parameter operation with no output schema, the description should clarify what a seed return value is and how it is presented. 'Returns the operation result' is too vague to tell an agent what it will receive or how to use it.

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% for the single image_id parameter, so the structured field already documents the input; the description adds no meaning about the image reference or its format. Baseline 3 applies when the schema does the heavy lifting.

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 largely restates the tool name: 'Run a synchronous Midjourney operation on RunAPI (get seed).' It never explains what a seed is or what retrieving it accomplishes, and does not differentiate this from siblings like image_to_prompt or get_task, which also touch Midjourney artifacts.

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 guidance on when to use this tool versus alternatives such as get_task (also waits on an operation) or image_to_prompt. The word 'synchronous' hints at a blocking call but no condition or exclusion is stated.

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 usefully discloses that the return contains both a status and a 'latest result payload', implying results may be absent while pending, but says nothing about auth requirements, rate limits, or what a non-terminal status looks like.

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 zero filler; the operation, the resource and the returned content are all conveyed without waste.

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 output schema and no annotations, the description does partially compensate by naming return contents (status, latest result payload). However, it leaves the async polling contract and terminal vs. pending status semantics undefined, which an agent needs for a task-status 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 100%, with task_id and the action enum both documented in the schema, so the baseline of 3 applies. The description adds no additional meaning about either parameter.

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 (task status and latest result payload) scoped to midjourney tasks, which is clear enough to distinguish it from creation endpoints like edit_image or text_to_image. It stops short of naming those siblings explicitly, so an agent must infer that this is the polling counterpart to 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?

There is no guidance on when to call this versus the creation tools; the async-polling workflow (call this after creating a task, using the returned task_id) is left entirely to inference. The word 'current' hints at repeated polling but never states it.

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, and it does disclose one genuine trait: the operation is synchronous, implying a blocking call that returns results directly rather than a task handle. Beyond that, it says nothing about permissions, cost, rate limits, or failure modes, and 'Returns the operation result' is circular, so the disclosure is thin.

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, front-loaded with the platform and mode, with no filler or repetition. It is efficient, though its brevity reflects under-specification rather than disciplined compression.

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 wraps an external Midjourney API call with no annotations and no output schema, so the description should explain the return shape, auth requirements, and limitations. Instead it gives an empty 'Returns the operation result' without saying whether the result is a prompt string, a task object, or a URL, leaving the agent under-informed for 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 reported at 100%, so the baseline of 3 applies even though the description adds no parameter detail. The single schema description ('Declared type: string') is largely uninformative, but the parameter name source_image_url is self-explanatory, so nothing critical is lost.

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 platform and a mode ('Run a synchronous Midjourney operation on RunAPI') plus the parenthetical '(image to prompt)', which mostly restates the tool name rather than explaining the action. It never says what 'image to prompt' actually produces (a text prompt derived from a source image) or how it differs from siblings like text_to_image or shorten_prompt. The purpose is inferable but only vaguely conveyed.

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 statement of prerequisites (API credentials, image constraints), and no routing against alternatives such as text_to_image, edit_image, or image_to_video. The agent must guess which tool applies to a given user intent.

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 burden. It does add real value by disclosing the return shape (task id, status, output URLs) despite there being no output schema, and it identifies the external RunAPI service. However it omits cost, async/polling behavior, permission needs, and what happens on timeout or failure.

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, front-loaded with the action and service, with the return contract last. No filler or redundancy.

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 10-parameter creation tool with no annotations and no output schema, the description is thin: it says nothing about the wait/poll to terminal status, timeout_ms, poll_interval_ms, callback_url, or model slug selection, all of which materially affect invocation. Only the return payload is covered.

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 80%, so the schema largely documents the parameters itself. The description adds no parameter-level meaning beyond implying a source image; the baseline 3 applies when the schema does the heavy lifting.

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 and resource ('Create a Midjourney task ... image to video') and names the backing service (RunAPI). The parenthetical scopes it to the image-to-video transform, which distinguishes it from text_to_image and extend_video among siblings, though it does not name those alternatives 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 statement of when to use this tool versus its siblings (extend_video, text_to_image, edit_image) or versus get_task for polling. The '(image to video)' hint implies a use case but gives no explicit selection criteria or prerequisites.

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?

With no annotations provided, the description carries the full burden, yet it only mentions synchronous execution and that a result is returned. It omits auth requirements, rate limits, whether the operation is billed, or what happens on failure — significant gaps for an API-backed 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, front-loaded with the action. It is efficient, though the brevity reflects under-specification rather than disciplined editing.

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 operation with no annotations and no output schema, the description should explain what the result looks like and any operational constraints. It says only that it returns 'the operation result', leaving the agent without enough to call it confidently.

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% for the single required 'prompt' parameter, so the schema does the documentation work and a baseline of 3 applies. The description adds no format, length, or content guidance beyond the schema.

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 largely restates the tool name ("shorten prompt") inside a generic wrapper phrase about running a Midjourney operation on RunAPI. It does not state what shortening a prompt means or how the result differs from siblings like image_to_prompt or text_to_image, so an agent gains little beyond the name itself.

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 indication of when to use this tool versus the many sibling image/prompt tools, no prerequisites, and no exclusions. The only implicit context is that it is a Midjourney operation, which is not enough to route selection.

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 burden. It does disclose that the call creates an asynchronous task and returns 'a task id, status, and output URLs', which is useful since no output schema exists, but it says nothing about cost/credit consumption, rate limits, or the wait/polling side effect that the schema exposes.

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, zero filler, with the core action front-loaded and the return contract appended. 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?

For an 8-parameter mutation tool with no annotations and no output schema, the description covers the action and the return shape but omits polling/wait semantics, model selection, and failure/timeout behaviour. Adequate but with clear gaps.

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 coverage is 75%, below the high-coverage baseline, and the description mentions no parameters at all. It never explains the wait/poll behaviour, model slug selection, timeout_ms, or callback_url, leaving the undocumented quarter of parameters without compensation.

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 gives a specific verb and resource ('Create a Midjourney task on RunAPI') plus the modality '(text to image)', which implicitly separates it from edit_image, image_to_video, and image_to_prompt. It never names a sibling or an explicit routing condition, so it falls short of the top mark.

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 use this tool versus edit_image, image_to_video, or image_to_prompt, and no prerequisites or exclusions. The agent must infer usage purely from the parenthetical modality hint.

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