Replicate Automation

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

16 stars

Best use case

Replicate Automation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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

Teams using Replicate Automation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/replicate-automation/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/data-ai/replicate-automation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/replicate-automation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Replicate Automation Compares

Feature / AgentReplicate AutomationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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](https://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

| Pitfall | Detail |
|---------|--------|
| Model-specific input keys | Each 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 encoding | `REPLICATE_CREATE_FILE` requires base64-encoded content. Binary files treated as text (UTF-8) will fail with decode errors. |
| Public vs deployment paths | Public models must be run via `REPLICATE_MODELS_PREDICTIONS_CREATE`. Using deployment-oriented paths causes HTTP 404 failures. |
| Sync wait limits | `wait_for` supports 1-60 seconds only. Long-running jobs need async handling via webhooks or polling `REPLICATE_PREDICTIONS_LIST`. |
| Image model constraints | Image 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 references | Heavy usage creates many uploads. Routinely check `REPLICATE_FILES_LIST` to avoid using stale `file_id` references. |

---

## Quick Reference

| Tool Slug | Description |
|-----------|-------------|
| `REPLICATE_MODELS_GET` | Get model details, schema, and metadata |
| `REPLICATE_MODELS_PREDICTIONS_CREATE` | Run a prediction on a model |
| `REPLICATE_CREATE_FILE` | Upload a file for model input |
| `REPLICATE_MODELS_README_GET` | Get model README documentation |
| `REPLICATE_MODELS_VERSIONS_LIST` | List all versions of a model |
| `REPLICATE_PREDICTIONS_LIST` | List prediction history with pagination |
| `REPLICATE_FILES_LIST` | List uploaded files |
| `REPLICATE_FILES_GET` | Get file details by ID |

---

*Powered by [Composio](https://composio.dev)*

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