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@runapi.ai/flux-kontext-mcp

by runapi-ai

Why This Package?

@runapi.ai/flux-kontext-mcp is a focused Model Context Protocol server for the Flux Kontext model line on RunAPI. It gives MCP-compatible assistants direct access to 1 endpoint and 2 model variants without loading the full RunAPI catalog.

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


Related MCP server: Image Generation MCP Server

Install

Add it to Claude Code:

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

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

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

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

{
  "mcpServers": {
    "flux-kontext": {
      "command": "npx",
      "args": ["-y", "@runapi.ai/flux-kontext-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

text_to_image

Yes

Create a Flux Kontext text to image 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 Flux Kontext model and endpoint.


Models

Flux Kontext covers 2 model variants across 1 endpoint. Each tool accepts the models listed for it:

Tool

Models

text_to_image

flux-kontext-max, flux-kontext-pro

Model availability can change between releases. Use check_pricing or the Flux Kontext 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 Flux Kontext text to image task with RunAPI.

The assistant can call check_pricing, then text_to_image, 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 Flux Kontext pricing, then create the task if it matches my request.

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


Configuration

The server resolves auth in this order:

  1. RUNAPI_API_KEY environment variable, useful for headless and CI hosts

  2. ~/.config/runapi/config.json, created by the MCP login tool or runapi login

  3. 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.


Resource

URL

Flux Kontext model page

https://runapi.ai/models/flux-kontext

npm package

@runapi.ai/flux-kontext-mcp

GitHub repository

runapi-ai/flux-kontext-mcp

RunAPI MCP overview

runapi.ai/mcp

RunAPI docs

runapi.ai/docs


License

Licensed under the Apache License, Version 2.0.

Available Tools

4 tools
check_pricingB

Look up RunAPI pricing for the flux-kontext model line.

ParametersJSON Schema
NameRequiredDescriptionDefault
modelNoModel slug. Defaults to the line's primary model.
actionNoEndpoint name. Defaults to the endpoint that offers the model.

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It only says 'look up' implying a read operation, but no details on permissions, side effects, or return behavior are given. The minimal description does not disclose behavioral traits beyond the name.

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 extraneous information. Every word contributes to the purpose.

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?

The description is minimal and does not explain default parameter behavior or output format. While the schema covers parameters, the tool description lacks completeness for a simple lookup without annotations or output 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 coverage is 100% with parameter descriptions already present. The tool description does not add any information about parameters beyond the schema, so a baseline of 3 is appropriate.

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: 'Look up RunAPI pricing for the flux-kontext model line.' It specifies the action (look up) and resource (pricing) and distinguishes from siblings like get_task and text_to_image.

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 vs alternatives, nor does it mention prerequisites or context. It merely states what it does, leaving the agent without context for selection.

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

get_taskA

Fetch the current status and latest result payload for a flux-kontext task.

ParametersJSON Schema
NameRequiredDescriptionDefault
actionNoAsynchronous endpoint the task was created on. Defaults to the line's only asynchronous endpoint.
task_idYesTask id returned when the task was created.

TDQS

A3.8/5.0
Behavior3/5

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

No annotations provided; description does not state it is a read-only operation or any constraints. 'Fetch' implies non-destructive behavior, but explicit mention would raise confidence.

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?

Single, well-formed sentence with no redundant words. Front-loaded with key action and resource.

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?

With simple params and no output schema, the description provides essential info (status + payload) but could specify the response structure or default behavior of the 'action' param.

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 coverage is 100% with descriptions for both parameters. The description does not add additional meaning beyond the schema, so baseline score 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 uses a specific verb ('Fetch') and resource ('task'), clearly indicating it retrieves status and result. It distinguishes from sibling tools like text_to_image (creation) and login/check_pricing.

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?

No explicit when-to-use or when-not-to-use guidance is given, but it's implied via context from sibling tool names. Could be improved by noting it should be called after creating a task via text_to_image.

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
NameRequiredDescriptionDefault
forceNoRe-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_imageB

Create a Flux Kontext task on RunAPI (text to image). Returns a task id, status, and output URLs.

ParametersJSON Schema
NameRequiredDescriptionDefault
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
promptYesImage description (English only).
watermarkNoWatermark identifier.
timeout_msNo
aspect_ratioNoOutput aspect ratio. Default: 16:9.
callback_urlNoWebhook URL for async notifications.
output_formatNoOutput format. Default: jpeg.
poll_interval_msNo
safety_toleranceNoContent safety threshold. 0-6 for generation, 0-2 for editing. Default: 2.
source_image_urlNoSource image URL for editing mode.
enable_translationNoAuto-translate non-English prompts. Default: true.
enable_prompt_expansionNoExpand the prompt with more detail. Default: false.

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the full disclosure burden, but it only says it creates a task and returns an id, status, and output URLs. It does not disclose that wait defaults to true and the call polls until terminal, that callback_url enables webhooks, or that source_image_url switches the operation from text-to-image to image editing.

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?

One sentence with no filler: it front-loads the action, names the resource, and lists key return values. It is concise and well-structured, though it sacrifices the additional context that a more complex tool would benefit from.

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?

For a 13-parameter asynchronous task API with polling, webhook callbacks, safety controls, translation, prompt expansion, and an editing mode, a one-line description is not complete. There is no output schema to fill the gap, and key orchestrational choices like default wait behavior and using get_task for later retrieval are absent.

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 85%, so the schema already documents 11 of 13 parameters; the description adds no per-parameter information beyond the general return shape. The two unclearly documented numeric parameters, timeout_ms and poll_interval_ms, are not clarified, but the high schema coverage justifies the baseline 3.

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 opens with the specific verb 'Create' and names the exact resource 'Flux Kontext task on RunAPI', then clarifies the use case with '(text to image)'. This clearly separates it from siblings like get_task, check_pricing, and login, which concern retrieval, pricing, and auth respectively.

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 use for generating a text-to-image task, but it does not state when to prefer this over get_task for polling/retrieving results. It also does not mention that providing source_image_url can invoke an editing mode, so the usage context is only partially implied.

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.

  1. 1 tool updatev0.1.13
    • Changedtext_to_image9 fields changed
      • removedInput schema / additionalProperties
        Removed value: -false
      • addedInput schema / properties / aspect_ratio / anyOf
        Added value: +[
        +  {
        +    "const": "21:9",
        +    "type": "string"
        +  },
        +  {
        +    "const": "16:9",
        +    "type": "string"
        +  },
        +  {
        +    "const": "4:3",
        +    "type": "string"
        +  },
        +  {
        +    "const": "1:1",
        +    "type": "string"
        +  },
        +  {
        +    "const": "3:4",
        +    "type": "string"
        +  },
        +  {
        +    "const": "9:16",
        +    "type": "string"
        +  }
        +]
      • removedInput schema / properties / aspect_ratio / enum
        Removed value: -[
        -  "21:9",
        -  "16:9",
        -  "4:3",
        -  "1:1",
        -  "3:4",
        -  "9:16"
        -]
      • removedInput schema / properties / aspect_ratio / type
        Removed value: -"string"
      • addedInput schema / properties / output_format / anyOf
        Added value: +[
        +  {
        +    "const": "jpeg",
        +    "type": "string"
        +  },
        +  {
        +    "const": "png",
        +    "type": "string"
        +  }
        +]
      • removedInput schema / properties / output_format / enum
        Removed value: -[
        -  "jpeg",
        -  "png"
        -]
      • removedInput schema / properties / output_format / type
        Removed value: -"string"
      • addedInput schema / properties / poll_interval_ms / maximum
        Added value: +9007199254740991
      • addedInput schema / properties / timeout_ms / maximum
        Added value: +9007199254740991
  2. 2 tool updatesv0.1.11
    • Changedget_task1 field changed
      • changedInput schema / properties / action / description
        Previous value: -"Endpoint the task was created on. Defaults to the line's only endpoint."New value: +"Asynchronous endpoint the task was created on. Defaults to the line's only asynchronous endpoint."
    • Changedtext_to_image9 fields changed
      • addedInput schema / properties / aspect_ratio / description
        Added value: +"Output aspect ratio. Default: 16:9."
      • addedInput schema / properties / callback_url / description
        Added value: +"Webhook URL for async notifications."
      • addedInput schema / properties / enable_prompt_expansion / description
        Added value: +"Expand the prompt with more detail. Default: false."
      • addedInput schema / properties / enable_translation / description
        Added value: +"Auto-translate non-English prompts. Default: true."
      • addedInput schema / properties / output_format / description
        Added value: +"Output format. Default: jpeg."
      • addedInput schema / properties / prompt / description
        Added value: +"Image description (English only)."
      • addedInput schema / properties / safety_tolerance / description
        Added value: +"Content safety threshold. 0-6 for generation, 0-2 for editing. Default: 2."
      • addedInput schema / properties / source_image_url / description
        Added value: +"Source image URL for editing mode."
      • addedInput schema / properties / watermark / description
        Added value: +"Watermark identifier."
  3. 1 tool updatev0.1.9
    • Addedlogin
  4. 2 tool updatesv0.1.2
    • Changedcheck_pricing1 field changed
      • changedInput schema / properties / action / description
        Previous value: -"Endpoint name. Defaults to the line's primary endpoint."New value: +"Endpoint name. Defaults to the endpoint that offers the model."
    • Changedtext_to_image5 fields changed
      • addedInput schema / properties / callback_url / type
        Added value: +"string"
      • addedInput schema / properties / prompt / type
        Added value: +"string"
      • addedInput schema / properties / source_image_url / type
        Added value: +"string"
      • addedInput schema / properties / watermark / type
        Added value: +"string"
      • addedInput schema / required
        Added value: +[
        +  "prompt"
        +]
  5. 3 tool updatesv0.1.0
    • First observedcheck_pricing
    • First observedget_task
    • First observedtext_to_image

TDQS

A3.8/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a distinct purpose: authentication, pricing lookup, task creation, and status retrieval. There is no overlap or ambiguity between the tools, allowing an agent to select the correct one without confusion.

Naming Consistency4/5

Tool names mostly follow a consistent snake_case verb_noun pattern (text_to_image, check_pricing, get_task). The 'login' tool is a single-word exception but is a common and recognizable auth action, so the overall consistency remains strong.

Tool Count5/5

With only 4 tools, the server is well-scoped for a focused flux-kontext image generation client. Each tool serves a necessary role (auth, pricing, creation, status) with no redundancy, making the count appropriate for the domain.

Completeness4/5

The essential workflow of authentication, task creation, and status retrieval is fully covered. Missing operations like cancel or listing past tasks are minor enhancements rather than critical gaps, so the surface is reasonably complete for primary use cases.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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