--- title: n8n Integration - AWS Bedrock Workflow Automation description: Connect n8n workflows to AWS Bedrock using stdapi.ai. Automate business processes with AI using 400+ integrations, no-code interface, and OpenAI-compatible or Anthropic-compatible nodes. keywords: n8n AI integration, workflow automation AI, no-code AI automation, AWS Bedrock workflows, business process automation, AI workflow tools, n8n AWS Bedrock, OpenAI n8n, Anthropic n8n --- # :material-sitemap: n8n Integration Connect n8n automation workflows to AWS Bedrock models through stdapi.ai's OpenAI-compatible or Anthropic-compatible interfaces. Existing OpenAI and Anthropic templates from the n8n marketplace work out of the box—simply point them to your stdapi.ai instance and access AWS Bedrock models. ## :material-information-outline: About n8n **🔗 Links:** [Website](https://n8n.io/) | [GitHub](https://github.com/n8n-io/n8n) | [Documentation](https://docs.n8n.io/) n8n is a powerful workflow automation platform that enables you to connect any app with an API to build intelligent automations. With its intuitive visual interface, you can create complex AI-powered workflows without writing code, connecting AWS Bedrock models to 400+ services including Slack, Google Sheets, Salesforce, and more. **Key Features:** - ⭐ **50,000+ GitHub stars** - Leading open-source workflow automation platform - **400+ integrations** - Pre-built nodes for popular services and APIs - **Visual no-code builder** - Drag-and-drop interface with JavaScript customization - **Self-hosted or cloud** - Deploy on your infrastructure or use n8n Cloud - **AI-native platform** - Built-in OpenAI nodes work instantly with AWS Bedrock via stdapi.ai - **Template marketplace** - Thousands of pre-built workflows ready to use ## :material-help-circle-outline: Why n8n + stdapi.ai?
- :material-puzzle: __Use Existing OpenAI Templates__
stdapi.ai works with n8n's OpenAI nodes. Thousands of marketplace templates and workflows designed for OpenAI run on AWS Bedrock—zero modifications needed. - :material-robot: __Use Existing Anthropic Templates__
stdapi.ai works with n8n's Anthropic nodes. Templates and workflows designed for Anthropic Claude run on AWS Bedrock—zero modifications needed. - :material-aws: __Access AWS Bedrock Models__
Claude, Nova, Llama, DeepSeek, Stable Diffusion, and 80+ models available in n8n workflows. Switch models without changing automation logic. - :material-graph-outline: __Automate Business Processes__
Connect AWS Bedrock AI to Slack, Salesforce, Google Workspace, databases, and 400+ services. Build intelligent automation with no-code drag-and-drop. - :material-lock: __Enterprise Data Control__
All AI processing stays in your AWS account. Self-host n8n and stdapi.ai for complete data sovereignty and compliance. - :material-currency-usd-off: __Pay-Per-Use Pricing__
No OpenAI subscriptions or per-automation fees. Pay only AWS Bedrock rates for actual AI usage in your workflows.
```mermaid %%{init: {'flowchart': {'htmlLabels': true}} }%% flowchart LR n8n[" n8n"] --> stdapi[" stdapi.ai"] stdapi --> bedrock[" AWS Bedrock"] stdapi --> transcribe[" AWS Transcribe"] stdapi --> polly[" AWS Polly"] ``` ## :material-check-circle: Prerequisites !!! info "What You'll Need" - ✓ **stdapi.ai deployed** - [See deployment guide](operations_getting_started.md) - ✓ **Your stdapi.ai URL** - e.g., `https://api.example.com` - ✓ **Your API key** - From Terraform output or configuration - ✓ **n8n instance** - Self-hosted or [n8n Cloud](https://n8n.io/cloud/) --- ## :material-cog: Configuration ### ![OpenAI](styles/logo_openai.svg){ style="height: 1.2em; vertical-align: text-bottom;" } OpenAI Nodes #### :material-key: Set Up Your Credentials The foundation of any n8n integration is configuring your API credentials. This one-time setup unlocks all AI capabilities. !!! example "Creating Your stdapi.ai Credential" **In your n8n interface:** 1. Navigate to **Credentials** menu 2. Click **Create Credential** 3. Search and select **"OpenAI"** in the credential list 4. Configure the following fields: ``` API Key: YOUR_STDAPI_KEY Base URL: https://YOUR_STDAPI_URL/v1 ``` !!! tip "What This Does" By setting a custom Base URL, you redirect all OpenAI API calls to your stdapi.ai instance. n8n will use this credential to authenticate and route requests to Amazon Bedrock models instead of OpenAI's servers. #### :material-cog-outline: Configure Nodes For each node, first select the credentials you previously created in the node parameters. Then, select the model you want to use. If you want to use a model that is not listed, you can enter its ID as an expression in the `Model` parameter. #### :material-chat-outline: Chat Completions Enables: Text generation and conversational AI in workflows. !!! example "Supported Node" **`OpenAI Chat Model`** - Model can be selected directly in the `Model` parameter - ⚠️ **Note:** `Use Responses API` parameter can optionally be checked — stdapi.ai now implements the `/v1/responses` endpoint. When unchecked, n8n uses the standard `/v1/chat/completions` endpoint instead. n8n calls either `POST /v1/chat/completions` (see [Chat Completions API](api_openai_chat_completions.md)) or `POST /v1/responses` (see [Responses API](api_openai_responses.md)) depending on this setting. Either way, the model must be a text/chat-capable model from the correct family. #### :material-message-text: Text Generation Enables: Text generation using the OpenAI Responses API. !!! example "Supported Node" **`OpenAI/Message a model`** - Model can be selected directly in the `Model` parameter n8n calls `POST /v1/responses` (see [Responses API](api_openai_responses.md)), so the model must be a text/chat-capable model from the correct family. #### :material-database: Embeddings Enables: Vector embeddings for semantic search and RAG workflows. !!! example "Supported Node" **`Embeddings OpenAI`** - Model can be selected directly in the `Model` parameter n8n calls `POST /v1/embeddings` (see [Embeddings API](api_openai_embeddings.md)), so the model must be an embeddings-capable model from the correct family. #### :material-image-search: Image Analysis Enables: Image understanding and analysis in workflows. !!! example "Supported Node" **`OpenAI/Analyze image`** - Model can be selected directly in the `Model` parameter n8n calls `POST /v1/responses` with image input (see [Responses API](api_openai_responses.md)), so the model must be a vision-capable model from the correct family. #### :material-image: Image Generation Enables: Text-to-image creation in workflows. !!! example "Supported Node" **`OpenAI/Generate an image`** - Model ID can be entered as expression in the `Model` parameter n8n calls `POST /v1/images/generations` (see [Images Generations API](api_openai_images_generations.md)), so the model must be an image-generation model from the correct family. #### :material-image-edit: Image Editing Enables: Image transformation and editing in workflows. !!! example "Supported Node" **`OpenAI/Edit image`** - Model ID can be entered as expression in the `Model` parameter n8n calls `POST /v1/images/edits` (see [Images Edits API](api_openai_images_edits.md)), so the model must be an image-editing model from the correct family. #### :material-volume-high: Audio Generation (TTS) Enables: Text-to-speech audio generation in workflows. !!! example "Supported Node" **`OpenAI/Generate audio`** - Model ID can be entered as expression in the `Model` parameter - **Or use OpenAI model names directly:** `tts-1` and `tts-1-hd` work by default thanks to built-in model aliases n8n calls `POST /v1/audio/speech` (see [Audio Speech API](api_openai_audio_speech.md)), so the model must match the text-to-speech modality and family. #### :material-microphone: Audio Transcription (STT) Enables: Speech-to-text transcription in workflows. !!! example "Supported Node" **`OpenAI/Transcribe a recording`** - Works out of the box with OpenAI's `whisper-1` model name - The model alias automatically maps to `amazon.transcribe` n8n calls `POST /v1/audio/transcriptions` (see [Audio Transcriptions API](api_openai_audio_transcriptions.md)), so the model must match the speech-to-text modality. #### :material-file-upload: Files Enables: Upload files once and reference them across multiple chat completion requests without resending the raw bytes each time. n8n calls the `/v1/files` endpoints (see [Files API](api_openai_files.md)). Set **Resource** to **"Files"** in the OpenAI node for all operations below. !!! example "Upload a file — `OpenAI/Upload a file`" Uploads a file to S3 and returns a `file_id` for use in subsequent requests. **Node parameters:** - **Resource:** Files - **Operation:** Upload a File - **Input Data Field Name:** name of the binary field containing the file - **Purpose:** intended purpose (e.g. `assistants`, `user_data`) **Typical workflow pattern:** 1. Receive or fetch a file (PDF, image, etc.) in an earlier node 2. Pass the binary data to this node 3. Store the returned `file_id` in a variable or database 4. Pass `file_id` in `OpenAI Chat Model` messages via the `type: "file"` content part for repeated analysis without re-uploading !!! example "Delete a file — `OpenAI/Delete a file`" Permanently deletes a file from S3 by its `file_id`. **Node parameters:** - **Resource:** Files - **Operation:** Delete a File - **File ID:** the `file_id` of the file to delete !!! example "List files — `OpenAI/List files`" Returns a paginated list of uploaded files, optionally filtered by purpose. **Node parameters:** - **Resource:** Files - **Operation:** List Files - **Purpose:** _(optional)_ filter results to a specific purpose - **Return All / Limit:** control pagination; enable **Return All** or set **Limit** for the first page Files are returned in descending order (newest first) by default. --- ### ![Anthropic](styles/logo_anthropic.svg){ style="height: 1.2em; vertical-align: text-bottom;" } Anthropic Nodes #### :material-key: Set Up Your Credentials !!! example "Creating Your stdapi.ai Anthropic Credential" **In your n8n interface:** 1. Navigate to **Credentials** menu 2. Click **Create Credential** 3. Search and select **"Anthropic"** in the credential list 4. Configure the following fields: ``` API Key: YOUR_STDAPI_KEY Base URL: https://YOUR_STDAPI_URL/anthropic ``` !!! tip "Anthropic Base URL" By default, all Anthropic-compatible routes are prefixed with `/anthropic`, so the Base URL must end with `/anthropic`. You can customize this prefix using the `ANTHROPIC_ROUTES_PREFIX` configuration variable documented in [Operations Configuration](operations_configuration.md#anthropic-routes-prefix). #### :material-cog-outline: Configure Nodes For each node, first select the credentials you previously created in the node parameters. Then, select the model you want to use. The model can be selected directly in the `Model` parameter for all supported nodes. #### :material-chat-outline: Chat Completions Enables: Text generation and conversational AI in workflows. !!! example "Supported Nodes" **`Anthropic Chat Model`** - Model can be selected directly in the `Model` parameter --- **`Anthropic/Message a model`** - Model can be selected directly in the `Model` parameter --- **`Message a model in Anthropic`** - Model can be selected directly in the `Model` parameter n8n calls `POST /anthropic/v1/messages` (see [Anthropic Messages API](api_anthropic_messages.md)), so the model must be a text/chat-capable model from the correct family. #### :material-image-search: Image Analysis Enables: Image understanding and analysis in workflows. !!! example "Supported Node" **`Anthropic/Analyze image`** - Model can be selected directly in the `Model` parameter n8n calls `POST /anthropic/v1/messages` with image content (see [Anthropic Messages API](api_anthropic_messages.md)), so the model must support vision capabilities. #### :material-file-document: Document Analysis Enables: Document understanding and extraction in workflows. !!! example "Supported Node" **`Anthropic/Analyze document`** - Model can be selected directly in the `Model` parameter n8n calls `POST /anthropic/v1/messages` with document content (see [Anthropic Messages API](api_anthropic_messages.md)), so the model must support document processing capabilities. #### :material-file-upload: Files Enables: Upload files once and reference them across multiple Messages requests as document or image sources. n8n calls the `/anthropic/v1/files` endpoints (see [Anthropic Files API](api_anthropic_files.md)). Set **Resource** to **"Files"** in the Anthropic node for all operations below. !!! example "Upload a file — `Anthropic/Upload a file`" Uploads a file to S3 and returns a `file_id` for use in subsequent Messages requests. **Node parameters:** - **Resource:** Files - **Operation:** Upload a File - **Input Data Field Name:** name of the binary field containing the file **Typical workflow pattern:** 1. Receive or fetch a file (PDF, image, etc.) in an earlier node 2. Pass the binary data to this node 3. Store the returned `file_id` in a variable or database 4. Pass `file_id` as a `source: {type: "file"}` in `Anthropic/Message a model` document or image blocks !!! example "Get file metadata — `Anthropic/Get file metadata`" Retrieves metadata (filename, MIME type, size, creation date) for a file by its `file_id`. **Node parameters:** - **Resource:** Files - **Operation:** Get File Metadata - **File ID:** the `file_id` of the file to retrieve !!! example "List files — `Anthropic/List files`" Returns a paginated list of uploaded files. **Node parameters:** - **Resource:** Files - **Operation:** List Files - **Return All / Limit:** control pagination; enable **Return All** or set **Limit** for the first page Files are returned in ascending order (oldest first). Use `after_id` / `before_id` cursors for bidirectional pagination. !!! example "Delete a file — `Anthropic/Delete a file`" Permanently deletes a file from S3 by its `file_id`. **Node parameters:** - **Resource:** Files - **Operation:** Delete a File - **File ID:** the `file_id` of the file to delete ## :material-arrow-right: Next Steps
- :material-rocket-launch: [**Getting Started**](operations_getting_started.md) — Deploy stdapi.ai to AWS with Terraform - :material-docker: [**Local Development**](operations_getting_started_local.md) — Run stdapi.ai locally with Docker - :material-puzzle: [**More Use Cases**](use_cases.md) — Explore other integrations and tools - :material-api: [**API Overview**](api_overview.md) — Explore supported endpoints