What can you do with this server?

A focused MCP server for generating videos using Hailuo AI models via the RunAPI platform. It provides four core capabilities: * Create text-to-video tasks (text_to_video): Generate a video from a text prompt using Hailuo text-to-video models (hailuo-02-text-to-video-pro, hailuo-02-text-to-video-standard), with configurable duration and optional polling until completion. * Create image-to-video tasks (image_to_video): Submit an image and generate a video using Hailuo image-to-video models (e.g., hailuo-02-image-to-video-pro/standard, hailuo-2.3-image-to-video-pro/standard), with options for duration (6 or 10 seconds), output resolution (512p, 768p, 1080p), and first/last frame image URLs. * Monitor task status (get_task): Retrieve the current status and results (including output URLs) for any previously submitted task using its task ID. * Check pricing (check_pricing): Look up current pricing for any Hailuo model and endpoint without requiring an API key, covering all model variants across both text-to-video and image-to-video endpoints.

How do I use hailuo-mcp?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@hailuo-mcp generate a video of a sunset over mountains" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

hailuo-mcp

by runapi-ai

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

Why This Package?

@runapi.ai/hailuo-mcp is a focused Model Context Protocol server for the Hailuo model line on RunAPI. It gives MCP-compatible assistants direct access to 2 endpoints and 6 model variants without loading the full RunAPI catalog.

Use this per-model server when an agent should stay scoped to Hailuo. Use @runapi.ai/mcp when one assistant should discover every RunAPI model line.

Related MCP server: @runapi.ai/gemini-omni-mcp

Install

Add it to Claude Code:

claude mcp add hailuo -s user -- npx -y @runapi.ai/hailuo-mcp

Use project scope when the server should be shared with a repository:

claude mcp add hailuo -s project -- npx -y @runapi.ai/hailuo-mcp

Codex, Cursor, Windsurf, VS Code, Roo Code, and other MCP hosts can use the same stdio command:

{
  "mcpServers": {
    "hailuo": {
      "command": "npx",
      "args": ["-y", "@runapi.ai/hailuo-mcp"]
    }
  }
}

check_pricing works before sign-in. For task creation and status polling, ask your assistant to call the login tool. It opens a browser login and saves credentials to ~/.config/runapi/config.json, the same file used by runapi login. Headless and CI hosts can still set RUNAPI_API_KEY before starting the MCP host.

Ready-made examples are in examples/ for Claude, Cursor, Windsurf, VS Code, and Roo Code.

Tools

Tool	Auth	Purpose
`image_to_video`	Yes	Create a Hailuo image to video task and optionally wait for a terminal status. Returns the task id, status, and output URLs.
`text_to_video`	Yes	Create a Hailuo text to video task and optionally wait for a terminal status. Returns the task id, status, and output URLs.
`get_task`	Yes	Fetch the current status and latest payload for an existing task.
`check_pricing`	No	Look up current pricing for a Hailuo model and endpoint.

Models

Hailuo covers 6 model variants across 2 endpoints. Each tool accepts the models listed for it:

Tool	Models
`image_to_video`	`hailuo-02-image-to-video-pro`, `hailuo-02-image-to-video-standard`, `hailuo-2.3-image-to-video-pro`, `hailuo-2.3-image-to-video-standard`
`text_to_video`	`hailuo-02-text-to-video-pro`, `hailuo-02-text-to-video-standard`

Model availability can change between releases. Use check_pricing or the Hailuo model page for the current catalog view.

Agent Prompts

Ask your assistant in natural language; it can inspect pricing, create the task, and return the task id plus output URLs.

Create a task

Run a Hailuo image to video task with RunAPI.

The assistant can call check_pricing, then image_to_video, and return the task id, status, and output URLs.

Submit without waiting

Create the task but don't wait for it to finish.

The assistant calls the create tool with wait: false and returns the task id. Check on it later with get_task.

Check pricing before creating

Check current Hailuo pricing, then create the task if it matches my request.

The assistant calls check_pricing and can link to the Hailuo model page for the canonical catalog entry.

Configuration

The server resolves auth in this order:

RUNAPI_API_KEY environment variable, useful for headless and CI hosts
~/.config/runapi/config.json, created by the MCP login tool or runapi login
No key, which still allows check_pricing

The config file is normally managed by login. A pre-provisioned headless config can use:

{
  "apiKey": "your_runapi_key"
}

Do not commit real API keys.

Links

Resource	URL
Hailuo model page	https://runapi.ai/models/hailuo
npm package	@runapi.ai/hailuo-mcp
GitHub repository	runapi-ai/hailuo-mcp
RunAPI MCP overview	runapi.ai/mcp
RunAPI docs	runapi.ai/docs

License

Licensed under the Apache License, Version 2.0.

Available Tools

5 tools

check_pricingC

Look up RunAPI pricing for the hailuo model line.

ParametersJSON Schema

Name	Required	Description	Default
`model`	No	Model slug. Defaults to the line's primary model.
`action`	No	Endpoint name. Defaults to the endpoint that offers the model.

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full behavioral burden and does not meet it. 'Look up' weakly implies a read-only query, but there is no statement about auth requirements, whether the price data is static or real-time, caching, cost of the call, or what is returned. For a pricing tool with zero annotation coverage this is a meaningful gap.

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

Conciseness4/5

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

A single front-loaded sentence with no wasted words, appropriate in size for a simple lookup. It is arguably under-specified rather than bloated, so the structure is sound.

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?

There is no output schema and no annotations, so the description is the sole source of behavioral and return-value context, and it omits both. An agent cannot tell what a pricing result looks like (currency, units, per-second vs per-call), how fresh it is, or what the hailuo scoping means for the optional parameters.

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 (model, action) are already documented with their defaults and enum values. The description adds the scoping hint that this is for the hailuo line, but no detail on slug format or how the two parameters interact. Baseline 3 is appropriate 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.

Purpose4/5

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 a named model line ('hailuo'), which no sibling offers. An agent can distinguish it from login, image_to_video, text_to_video, and get_task without opening the schema. It stops short of explicitly contrasting with siblings, but none are close enough to require it.

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 gives no when-to-use guidance, no prerequisites, and no conditions under which this tool should be preferred or avoided. The only inference an agent can draw is that pricing is checked before invoking a video endpoint, which is never stated.

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

get_taskB

Fetch the current status and latest result payload for a hailuo task.

ParametersJSON Schema

Name	Required	Description	Default
`action`	Yes	Asynchronous endpoint the task was created on.
`task_id`	Yes	Task id returned when the task was created.

TDQS

B3.1/5.0

Behavior2/5

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 what is retrieved (status and latest result payload), but says nothing about permissions, rate limits, polling behavior, error handling, 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 a single, front-loaded sentence with no filler. Every word contributes to stating what the tool fetches.

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

Completeness3/5

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

For a simple two-parameter read tool with full schema coverage, the description adequately states what is returned. However, it omits usage context and behavioral traits that would help an agent unfamiliar with the async task ecosystem, and there is no output schema or annotation to fill those gaps.

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%, and both parameters are fully documented in the input schema. The description adds no parameter detail, so the baseline of 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.

Purpose4/5

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

The description gives a specific verb (Fetch) and resource (current status and latest result payload) and scopes it to a hailuo task. It implies retrieval of an existing task for the image_to_video/text_to_video siblings, but does not explicitly name or differentiate from those alternatives.

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?

There is no explicit guidance on when to use this tool versus alternatives; the only hint is that task_id and action imply polling after an async task is created. No conditions, prerequisites, or exclusions are stated.

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

image_to_videoB

Create a Hailuo task on RunAPI (image to video). Returns a task id, status, and output URLs.

ParametersJSON Schema

Name	Required	Description
`wait`	No	Poll until the task reaches a terminal status.
`model`	No	RunAPI model slug for this model line.
`prompt`	No	Declared type: string.
`timeout_ms`	No
`callback_url`	No	Declared type: string.
`duration_seconds`	No	Declared type: integer.
`poll_interval_ms`	No
`prompt_optimizer`	No	Declared type: boolean.
`output_resolution`	No	Declared type: string.
`last_frame_image_url`	No	Declared type: string.
`enable_safety_checker`	No	Enable the safety checker. Declared type: boolean.
`first_frame_image_url`	Yes	Declared type: string.

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose that this is an asynchronous task-creation endpoint returning a task id and status, which is genuinely useful. However, it omits the blocking behavior implied by the wait parameter default, timeout semantics, cost implications, and the fact that the returned URLs may not be immediately available.

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

Conciseness4/5

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

Two short sentences, front-loaded with the action and platform, with the return shape in the second sentence. Nothing is wasted, though the parenthetical 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.

Completeness3/5

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

For a 12-parameter, no-annotation, no-output-schema tool, the description usefully covers the return values, which compensates for the missing output schema. But it leaves key generation controls (duration, resolution, prompt, last-frame image) and the polling/timeout behavior entirely to the schema.

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 83%, above the 80% threshold, so the schema already documents nearly all parameters. The description adds no per-parameter meaning (model slug, duration_seconds, output_resolution, prompt are unexplained), so baseline 3 applies.

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?

States a specific verb (Create), the resource (a Hailuo task on RunAPI), and the modality (image to video), which separates it from the sibling text_to_video. It stops short of naming that sibling explicitly, so it is clear but not fully differentiated.

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

Usage Guidelines3/5

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

The parenthetical '(image to video)' implies the usage context and the existence of the text_to_video alternative, but the description never states when to pick this tool over that one, nor any prerequisites such as image URL accessibility or account/auth needs.

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

loginA

Authenticate RunAPI by opening a browser PKCE login flow and saving the API key to ~/.config/runapi/config.json.

ParametersJSON Schema

Name	Required	Description	Default
`force`	No	Re-run browser login when the current credential comes from the local config file.

TDQS

A4/5.0

Behavior4/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines3/5

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.

text_to_videoB

Create a Hailuo task on RunAPI (text to video). Returns a task id, status, and output URLs.

ParametersJSON Schema

Name	Required	Description
`wait`	No	Poll until the task reaches a terminal status.
`model`	No	RunAPI model slug for this model line.
`prompt`	No	Declared type: string.
`timeout_ms`	No
`callback_url`	No	Declared type: string.
`duration_seconds`	No	Declared type: integer.
`poll_interval_ms`	No
`prompt_optimizer`	No	Declared type: boolean.
`enable_safety_checker`	No	Declared type: boolean.

TDQS

B3.2/5.0

Behavior3/5

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

No annotations are provided, so the description carries full burden. It usefully discloses that this is asynchronous task creation returning a task id and status, plus the schema's 'wait' default of polling to terminal status. However it omits auth requirements, rate limits, and what happens if wait is false (fire-and-forget vs. polling), leaving meaningful behavioral gaps.

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

Conciseness4/5

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

Two tight sentences with the core action front-loaded and no wasted words. It is appropriately sized, though it sacrifices some useful detail for brevity.

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

Completeness3/5

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

With 9 parameters and no output schema or annotations, the description is only partially sufficient. It helpfully names the return shape (task id, status, output URLs), but does not explain the wait/poll/callback interaction an agent needs to drive this async tool correctly.

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 78%, close to the high-coverage baseline, so the schema already documents most parameters. The description adds nothing about parameters (prompt content, duration, safety checker, callback), so baseline 3 is appropriate.

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?

States a specific verb (Create) and resource (a Hailuo task on RunAPI) and disambiguates from the sibling image_to_video with '(text to video)'. It is clear what the tool produces, though the 'Hailuo/RunAPI' naming adds external context that isn't further explained.

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?

There is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives. The sibling get_task clearly exists for polling results, yet the description never routes the agent there or explains the relationship between creating a task and retrieving it.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

4 tool updatesv0.3.0Oct 5, 2026
- Changedcheck_pricing2 fields changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
  - removedInput schema / properties / model / enum
```
Removed value: -[
-  "hailuo-02-image-to-video-pro",
-  "hailuo-02-image-to-video-standard",
-  "hailuo-2.3-image-to-video-pro",
-  "hailuo-2.3-image-to-video-standard",
-  "hailuo-02-text-to-video-pro",
-  "hailuo-02-text-to-video-standard"
-]
```
- Changedget_task1 field changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
- Changedimage_to_video13 fields changed
  - changedInput schema / additionalProperties
```
Previous value: -falseNew value: +{}
```
  - addedInput schema / properties / callback_url / description
```
Added value: +"Declared type: string."
```
  - addedInput schema / properties / duration_seconds / description
```
Added value: +"Declared type: integer."
```
  - changedInput schema / properties / duration_seconds / type
```
Previous value: -"number"New value: +"integer"
```
  - addedInput schema / properties / enable_safety_checker / description
```
Added value: +"Enable the safety checker. Declared type: boolean."
```
  - addedInput schema / properties / first_frame_image_url / description
```
Added value: +"Declared type: string."
```
  - addedInput schema / properties / last_frame_image_url / description
```
Added value: +"Declared type: string."
```
  - removedInput schema / properties / model / enum
```
Removed value: -[
-  "hailuo-02-image-to-video-pro",
-  "hailuo-02-image-to-video-standard",
-  "hailuo-2.3-image-to-video-pro",
-  "hailuo-2.3-image-to-video-standard"
-]
```
  - addedInput schema / properties / output_resolution / description
```
Added value: +"Declared type: string."
```
  - addedInput schema / properties / poll_interval_ms / maximum
```
Added value: +9007199254740991
```
  - addedInput schema / properties / prompt / description
```
Added value: +"Declared type: string."
```
  - addedInput schema / properties / prompt_optimizer / description
```
Added value: +"Declared type: boolean."
```
  - addedInput schema / properties / timeout_ms / maximum
```
Added value: +9007199254740991
```
- Changedtext_to_video11 fields changed
  - changedInput schema / additionalProperties
```
Previous value: -falseNew value: +{}
```
  - addedInput schema / properties / callback_url / description
```
Added value: +"Declared type: string."
```
  - addedInput schema / properties / duration_seconds / description
```
Added value: +"Declared type: integer."
```
  - changedInput schema / properties / duration_seconds / type
```
Previous value: -"number"New value: +"integer"
```
  - addedInput schema / properties / enable_safety_checker / description
```
Added value: +"Declared type: boolean."
```
  - removedInput schema / properties / model / enum
```
Removed value: -[
-  "hailuo-02-text-to-video-pro",
-  "hailuo-02-text-to-video-standard"
-]
```
  - addedInput schema / properties / poll_interval_ms / maximum
```
Added value: +9007199254740991
```
  - addedInput schema / properties / prompt / description
```
Added value: +"Declared type: string."
```
  - addedInput schema / properties / prompt_optimizer / description
```
Added value: +"Declared type: boolean."
```
  - addedInput schema / properties / timeout_ms / maximum
```
Added value: +9007199254740991
```
  - addedInput schema / required
```
Added value: +[]
```
3 tool updatesv0.1.7Aug 5, 2026
- Changedget_task1 field changed
  - changedInput schema / properties / action / description
```
Previous value: -"Endpoint the task was created on."New value: +"Asynchronous endpoint the task was created on."
```
- Changedimage_to_video9 fields changed
  - addedInput schema / properties / callback_url
```
Added value: +{
+  "type": "string"
+}
```
  - removedInput schema / properties / duration_seconds / enum
```
Removed value: -[
-  6,
-  10
-]
```
  - addedInput schema / properties / enable_safety_checker
```
Added value: +{
+  "type": "boolean"
+}
```
  - addedInput schema / properties / first_frame_image_url / type
```
Added value: +"string"
```
  - addedInput schema / properties / last_frame_image_url / type
```
Added value: +"string"
```
  - removedInput schema / properties / output_resolution / enum
```
Removed value: -[
-  "512p",
-  "768p",
-  "1080p"
-]
```
  - addedInput schema / properties / prompt
```
Added value: +{
+  "type": "string"
+}
```
  - addedInput schema / properties / prompt_optimizer
```
Added value: +{
+  "type": "boolean"
+}
```
  - addedInput schema / required
```
Added value: +[
+  "first_frame_image_url"
+]
```
- Changedtext_to_video5 fields changed
  - addedInput schema / properties / callback_url
```
Added value: +{
+  "type": "string"
+}
```
  - removedInput schema / properties / duration_seconds / enum
```
Removed value: -[
-  6,
-  10
-]
```
  - addedInput schema / properties / enable_safety_checker
```
Added value: +{
+  "type": "boolean"
+}
```
  - addedInput schema / properties / prompt
```
Added value: +{
+  "type": "string"
+}
```
  - addedInput schema / properties / prompt_optimizer
```
Added value: +{
+  "type": "boolean"
+}
```
1 tool updatev0.1.6Jul 13, 2026
- Addedlogin
4 tool updatesv0.1.0Jun 24, 2026
- First observedcheck_pricing
- First observedget_task
- First observedimage_to_video
- First observedtext_to_video

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.5/5.0

Scored 2026-10-05 07:45 across 5 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: two generation tools differ by input modality (image_to_video vs text_to_video), get_task handles retrieval, and login/check_pricing are distinct utilities. There is no meaningful overlap that would cause misselection.

Naming Consistency4/5

Almost all tools use snake_case with a verb_noun or noun_to_noun structure (check_pricing, image_to_video, text_to_video, get_task), which is readable and consistent. 'login' is a bare verb that breaks the noun pattern slightly, but this is a conventional deviation.

Tool Count5/5

Five tools is well-scoped for a video-generation service, with each tool earning its place: auth, pricing, two generation modes, and task polling. Nothing feels redundant or missing from the count perspective.

Completeness4/5

Core lifecycle is covered: login, check pricing, create tasks in both modes, and poll task status/results. Minor gaps exist such as no task cancellation or listing of prior tasks, but the primary workflow is complete.

Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

Need Help?

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maintenance
RunAPI MCP server for the Flux 2 model line. Create tasks, poll their status, and check pricing through a single RunAPI API key.
Updated 8 days ago (2026-09-30 11:30 UTC)
5
272 npm
Apache 2.0
@runapi.ai/gemini-omni-mcp
AI & Machine Learning Multimedia Processing
runapi-ai
A
license
A
quality
A
maintenance
MCP server for the Gemini Omni model line, enabling task creation (audio, character, text-to-video) and pricing checks through RunAPI.
Updated 8 days ago (2026-09-30 11:30 UTC)
6
289 npm
Apache 2.0
imagen-4-mcp
AI & Machine Learning Image & Video Processing
runapi-ai
A
license
A
quality
A
maintenance
RunAPI MCP server for the Imagen 4 model line. Create tasks, poll their status, and check pricing through a single RunAPI API key.
Updated 8 days ago (2026-09-30 11:34 UTC)
5
254 npm
Apache 2.0
infinitetalk-mcp
AI & Machine Learning Multimedia Processing
runapi-ai
A
license
B
quality
A
maintenance
MCP server for the InfiniteTalk model line, enabling audio-to-video task creation, status polling, and pricing checks via a RunAPI API key.
Updated 8 days ago (2026-09-30 11:34 UTC)
4
261 npm
1
Apache 2.0

Why This Package?

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@runapi.ai/flux-2-mcpofficial