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ComposioHQ

Automate Replicate AI model operations -- run predictions, upload files, inspect model schemas, list versions, and manage prediction history via the Composio MC

 
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Automate Replicate AI model operations -- run predictions, upload files, inspect model schemas, list versions, and manage prediction history via the Composio MCP integration.

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SKILL.md

name: Replicate Automation description: "Automate Replicate AI model operations -- run predictions, upload files, inspect model schemas, list versions, and manage prediction history via the Composio MCP integration." requires: mcp: - rube

Replicate Automation

Automate your Replicate AI model workflows -- run predictions on any public model (image generation, LLMs, audio, video), upload input files, inspect model schemas and documentation, list model versions, and track prediction history.

Toolkit docs: composio.dev/toolkits/replicate


Setup

  1. Add the Composio MCP server to your client: https://rube.app/mcp
  2. Connect your Replicate account when prompted (API token authentication)
  3. Start using the workflows below

Core Workflows

1. Get Model Details and Schema

Use REPLICATE_MODELS_GET to inspect a model's input/output schema before running predictions.

Tool: REPLICATE_MODELS_GET
Inputs:
  - model_owner: string (required) -- e.g., "meta", "black-forest-labs", "stability-ai"
  - model_name: string (required) -- e.g., "meta-llama-3-8b-instruct", "flux-1.1-pro"

Important: Each model has unique input keys and types. Always check the openapi_schema from this response before constructing prediction inputs.

2. Run a Prediction

Use REPLICATE_MODELS_PREDICTIONS_CREATE to run inference on any model with optional synchronous waiting and webhooks.

Tool: REPLICATE_MODELS_PREDICTIONS_CREATE
Inputs:
  - model_owner: string (required) -- e.g., "meta", "black-forest-labs"
  - model_name: string (required) -- e.g., "flux-1.1-pro", "sdxl"
  - input: object (required) -- model-specific inputs, e.g., { "prompt": "A sunset over mountains" }
  - wait_for: integer (1-60 seconds, optional) -- synchronous wait for completion
  - cancel_after: string (optional) -- max execution time, e.g., "300s", "5m"
  - webhook: string (optional) -- HTTPS URL for async completion notifications
  - webhook_events_filter: array (optional) -- ["start", "output", "logs", "completed"]

Sync vs Async: Use wait_for (1-60s) for fast models. For long-running jobs, omit it and use webhooks or poll via REPLICATE_PREDICTIONS_LIST.

3. Upload Files for Model Input

Use REPLICATE_CREATE_FILE to upload images, documents, or other binary inputs that models need.

Tool: REPLICATE_CREATE_FILE
Inputs:
  - content: string (required) -- base64-encoded file content
  - filename: string (required) -- e.g., "input.png", "audio.wav" (max 255 bytes UTF-8)
  - content_type: string (default "application/octet-stream") -- MIME type
  - metadata: object (optional) -- custom JSON metadata

4. Read Model Documentation

Use REPLICATE_MODELS_README_GET to access a model's README in Markdown format for detailed usage instructions.

Tool: REPLICATE_MODELS_README_GET
Inputs:
  - model_owner: string (required)
  - model_name: string (required)

5. List Model Versions

Use REPLICATE_MODELS_VERSIONS_LIST to see all available versions of a model, sorted newest first.

Tool: REPLICATE_MODELS_VERSIONS_LIST
Inputs:
  - model_owner: string (required)
  - model_name: string (required)

6. Track Prediction History and Files

Use REPLICATE_PREDICTIONS_LIST to retrieve prediction history, and REPLICATE_FILES_GET/REPLICATE_FILES_LIST to manage uploaded files.

Tool: REPLICATE_PREDICTIONS_LIST
  - Lists all predictions for the authenticated user with pagination

Tool: REPLICATE_FILES_LIST
  - Lists uploaded files, most recent first

Tool: REPLICATE_FILES_GET
  - Get details of a specific file by ID

Known Pitfalls

PitfallDetail
Model-specific input keysEach model has unique input keys and types. Using the wrong key causes validation errors. Always call REPLICATE_MODELS_GET first to check the openapi_schema.
File upload encodingREPLICATE_CREATE_FILE requires base64-encoded content. Binary files treated as text (UTF-8) will fail with decode errors.
Public vs deployment pathsPublic models must be run via REPLICATE_MODELS_PREDICTIONS_CREATE. Using deployment-oriented paths causes HTTP 404 failures.
Sync wait limitswait_for supports 1-60 seconds only. Long-running jobs need async handling via webhooks or polling REPLICATE_PREDICTIONS_LIST.
Image model constraintsImage models like flux-1.1-pro have specific constraints (e.g., max width/height 1440px, valid aspect ratios). Check the model schema first.
Stale file referencesHeavy usage creates many uploads. Routinely check REPLICATE_FILES_LIST to avoid using stale file_id references.

Quick Reference

Tool SlugDescription
REPLICATE_MODELS_GETGet model details, schema, and metadata
REPLICATE_MODELS_PREDICTIONS_CREATERun a prediction on a model
REPLICATE_CREATE_FILEUpload a file for model input
REPLICATE_MODELS_README_GETGet model README documentation
REPLICATE_MODELS_VERSIONS_LISTList all versions of a model
REPLICATE_PREDICTIONS_LISTList prediction history with pagination
REPLICATE_FILES_LISTList uploaded files
REPLICATE_FILES_GETGet file details by ID

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