Runware MCP connector

1. Install the SDK

   Node.js

   npm install @scalekit-sdk/node

   Python

   pip install scalekit

   Full SDK reference: Node.js | Python

2. Set your credentials

   Add your Scalekit credentials to your .env file. Find values in app.scalekit.com > Developers > API Credentials.

   .env

   SCALEKIT_ENVIRONMENT_URL=<your-environment-url>
   SCALEKIT_CLIENT_ID=<your-client-id>
   SCALEKIT_CLIENT_SECRET=<your-client-secret>

3. Authorize and make your first call

   Node.js

   quickstart.ts

   import { ScalekitClient } from '@scalekit-sdk/node'
   import 'dotenv/config'
   
   const scalekit = new ScalekitClient(
     process.env.SCALEKIT_ENV_URL,
     process.env.SCALEKIT_CLIENT_ID,
     process.env.SCALEKIT_CLIENT_SECRET,
   )
   const actions = scalekit.actions
   
   const connector = 'runwaremcp'
   const identifier = 'user_123'
   
   // Generate an authorization link for the user
   const { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })
   console.log('Authorize Runware MCP:', link)
   process.stdout.write('Press Enter after authorizing...')
   await new Promise(r => process.stdin.once('data', r))
   
   // Make your first call
   const result = await actions.executeTool({
     connector,
     identifier,
     toolName: 'runwaremcp_list_capabilities',
     toolInput: {},
   })
   console.log(result)

   Python

   quickstart.py

   import os
   from scalekit.client import ScalekitClient
   from dotenv import load_dotenv
   load_dotenv()
   
   scalekit_client = ScalekitClient(
       env_url=os.getenv("SCALEKIT_ENV_URL"),
       client_id=os.getenv("SCALEKIT_CLIENT_ID"),
       client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
   )
   actions = scalekit_client.actions
   
   connection_name = "runwaremcp"
   identifier = "user_123"
   
   # Generate an authorization link for the user
   link_response = actions.get_authorization_link(
       connection_name=connection_name,
       identifier=identifier,
   )
   print("Authorize Runware MCP:", link_response.link)
   input("Press Enter after authorizing...")
   
   # Make your first call
   result = actions.execute_tool(
       tool_input={},
       tool_name="runwaremcp_list_capabilities",
       connection_name=connection_name,
       identifier=identifier,
   )
   print(result)

What you can do

Connect this agent connector to let your agent:

• Run records — Run an AI inference task on Runware
• Upload model, image — Upload a custom AI model to Runware (checkpoint, LoRA, VAE, embeddings, etc.)
• Search model — Search Runware’s Civitai mirror and community-uploaded models — third-party fine-tunes, user uploads, style LoRAs, custom checkpoints
• Schema model — Get the parameter schema for a specific model
• Pricing model — Get pricing details for a curated Runware model — overview text plus example configurations with prices (e.g
• Examples model — Get sample input/output examples for a curated Runware model

Tool list

Use the exact tool names from the Tool list below when you call execute_tool. If you’re not sure which name to use, list the tools available for the current user first.

runwaremcp_account#Retrieve Runware account information including balance and usage.2 params▾

Retrieve Runware account information including balance and usage.

NameTypeRequiredDescription

operationstringrequiredWhich account operation to perform. Currently only "getDetails" is supported.

includeCostbooleanoptionalInclude cost information

runwaremcp_get_task_details#Retrieve the original request and response for a previously executed task. Useful for recovering results or auditing past generations.1 param▾

Retrieve the original request and response for a previously executed task. Useful for recovering results or auditing past generations.

NameTypeRequiredDescription

taskUUIDstringrequiredUUID of the task to retrieve

runwaremcp_image_upload#Upload an image to Runware for use as input in subsequent generation tasks. Returns an image UUID that can be used as seedImage, maskImage, etc.1 param▾

Upload an image to Runware for use as input in subsequent generation tasks. Returns an image UUID that can be used as seedImage, maskImage, etc.

NameTypeRequiredDescription

imagestringrequiredURL, data URI, or base64 of the image to upload

runwaremcp_list_capabilities#List every model capability Runware supports, with their human-readable labels. Use this to discover the taxonomy (e.g. "io:text-to-image", "op:upscale") before filtering list_models by capability, or to answer "what can Runware do?".0 params▾

List every model capability Runware supports, with their human-readable labels. Use this to discover the taxonomy (e.g. "io:text-to-image", "op:upscale") before filtering list_models by capability, or to answer "what can Runware do?".

runwaremcp_list_models#List Runware's official, curated model integrations. Returns each model's name, AIR identifier, headline, capabilities, and pricing. Call this FIRST whenever the user names or asks about a model that could be first-party (e.g. "FLUX 2 dev", "SDXL", "Veo 3", "Gemma", "Wan 2.5", "Z-Image"), and also for open-ended "what models are available?" questions. Match the user's named model against the returned names. Only fall through to model_search if no curated entry matches.4 params▾

List Runware's official, curated model integrations. Returns each model's name, AIR identifier, headline, capabilities, and pricing. Call this FIRST whenever the user names or asks about a model that could be first-party (e.g. "FLUX 2 dev", "SDXL", "Veo 3", "Gemma", "Wan 2.5", "Z-Image"), and also for open-ended "what models are available?" questions. Match the user's named model against the returned names. Only fall through to model_search if no curated entry matches.

NameTypeRequiredDescription

capabilitystringoptionalOptional capability filter (e.g. "io:text-to-image", "op:upscale"). Use list_capabilities first to discover valid ids.

categorystringoptionalOptional output-modality filter

creatorstringoptionalOptional creator id filter (e.g. "google", "alibaba")

searchstringoptionalOptional free-text search across name, AIR, creator, capabilities

runwaremcp_model_details#Get the full curated metadata for a single Runware model by AIR identifier — name, headline, description, capabilities, pricing, and creator. Use this when the user wants more depth on a model already surfaced by list_models, or to confirm an AIR matches what the user named.1 param▾

Get the full curated metadata for a single Runware model by AIR identifier — name, headline, description, capabilities, pricing, and creator. Use this when the user wants more depth on a model already surfaced by list_models, or to confirm an AIR matches what the user named.

NameTypeRequiredDescription

airstringrequiredModel AIR identifier (e.g. "runware:400@1")

runwaremcp_model_examples#Get sample input/output examples for a curated Runware model. Useful when the user wants to see what a model produces, or to crib a working request shape before constructing a run() call.2 params▾

Get sample input/output examples for a curated Runware model. Useful when the user wants to see what a model produces, or to crib a working request shape before constructing a run() call.

NameTypeRequiredDescription

airstringrequiredModel AIR identifier

capabilitystringoptionalOptional capability filter (e.g. "io:text-to-image")

runwaremcp_model_pricing#Get pricing details for a curated Runware model — overview text plus example configurations with prices (e.g. "1024×1024 = $0.0032"). Use this when the user asks how much a specific model will cost.1 param▾

Get pricing details for a curated Runware model — overview text plus example configurations with prices (e.g. "1024×1024 = $0.0032"). Use this when the user asks how much a specific model will cost.

NameTypeRequiredDescription

airstringrequiredModel AIR identifier

runwaremcp_model_schema#Get the parameter schema for a specific model. Returns the JSON Schema describing all accepted parameters, their types, defaults, and constraints. ALWAYS call this before calling run() with a model you haven't used before, so you know what parameters to pass.1 param▾

Get the parameter schema for a specific model. Returns the JSON Schema describing all accepted parameters, their types, defaults, and constraints. ALWAYS call this before calling run() with a model you haven't used before, so you know what parameters to pass.

NameTypeRequiredDescription

modelstringrequiredModel AIR identifier (e.g., "runware:400@1", "google:3@3", "google:gemma@4-31b")

runwaremcp_model_search#Search Runware's Civitai mirror and community-uploaded models — third-party fine-tunes, user uploads, style LoRAs, custom checkpoints. ONLY use this AFTER list_models has been checked and the user's named model is not in the curated catalog, OR when the user explicitly asks for a Civitai or community model. Do NOT use this for first-party models like FLUX, SDXL, Veo, Imagen, Gemma, Wan, Z-Image — those live in list_models.5 params▾

Search Runware's Civitai mirror and community-uploaded models — third-party fine-tunes, user uploads, style LoRAs, custom checkpoints. ONLY use this AFTER list_models has been checked and the user's named model is not in the curated catalog, OR when the user explicitly asks for a Civitai or community model. Do NOT use this for first-party models like FLUX, SDXL, Veo, Imagen, Gemma, Wan, Z-Image — those live in list_models.

NameTypeRequiredDescription

searchstringrequiredSearch query (name, description, or AIR ID)

architecturestringoptionalFilter by architecture (e.g. "flux-1-dev", "sdxl")

categorystringoptionalFilter by model category

tagsarrayoptionalFilter by tags

typestringoptionalFilter checkpoints by type (only when category=checkpoint)

runwaremcp_model_upload#Upload a custom AI model to Runware (checkpoint, LoRA, VAE, embeddings, etc.). Returns the AIR identifier once the upload completes.7 params▾

Upload a custom AI model to Runware (checkpoint, LoRA, VAE, embeddings, etc.). Returns the AIR identifier once the upload completes.

NameTypeRequiredDescription

architecturestringrequiredModel architecture (e.g. "flux-1-dev", "sdxl")

categorystringrequiredModel category

downloadURLstringrequiredURL where the model weights can be downloaded from

formatstringrequiredWeight file format

namestringrequiredDisplay name for the model

versionstringrequiredModel version

airstringoptionalOptional AIR identifier (format: provider:model@version)

runwaremcp_run#Run an AI inference task on Runware. Supports image generation, video generation, audio generation, 3D generation, upscaling, background removal, captioning, and more. Pass a model AIR identifier and task-specific parameters. Example: { "model": "runware:400@1", "positivePrompt": "a cat", "width": 1024, "height": 1024 }1 param▾

Run an AI inference task on Runware. Supports image generation, video generation, audio generation, 3D generation, upscaling, background removal, captioning, and more. Pass a model AIR identifier and task-specific parameters. Example: { "model": "runware:400@1", "positivePrompt": "a cat", "width": 1024, "height": 1024 }

NameTypeRequiredDescription

modelstringrequiredModel AIR identifier (e.g., "runware:400@1" for image, "google:3@3" for video, "google:gemma@4-31b" for LLM)