docs: Remove deprecated PyAirbyte Fast-Coder MCP and deprioritize embedded/sonar links (#69743)
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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Aaron ("AJ") Steers
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@@ -6,13 +6,12 @@ products: embedded
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Airbyte provides multiple tools to help you build data applications.
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- **Airbyte Embedded Widget**: App development teams who have signed up for Airbyte Embedded and are looking to get started onboarding customers using the Embedded Widget can follow the get started guide at the bottom of this page, which will step you through a complete sample onboarding app.
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- **Authentication Proxies**: Connect safely to third party APIs using Airbyte's Authentication Proxies.
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- **MCP Servers**: Airbyte provides multiple MCP (Model Context Protocol) servers for different use cases:
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- [**PyAirbyte MCP**](#pyairbyte-mcp): Local MCP server for managing Airbyte connectors through AI assistants.
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- [**Connector Builder MCP**](#connector-builder-mcp): AI-assisted connector development - _**coming soon!**_
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- [**Embedded Operator MCP**](#embedded-operator-mcp): Manage embedded configurations and pipelines.
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- [**PyAirbyte Fast-Coder MCP**](#pyairbyte-fast-coder-mcp) _(deprecated)_: Remote MCP server for rapid pipeline code generation.
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- **Airbyte Embedded Widget**: App development teams who have signed up for Airbyte Embedded and are looking to get started onboarding customers using the Embedded Widget can follow the get started guide at the bottom of this page, which will step you through a complete sample onboarding app.
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- **Authentication Proxies**: Connect safely to third party APIs using Airbyte's Authentication Proxies.
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## Prerequisites
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@@ -48,13 +47,10 @@ Airbyte provides multiple MCP (Model Context Protocol) servers to enable AI-assi
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[The Embedded Operator MCP](./embedded/operator-mcp/README.md) is a remote MCP server providing tools that enable managing embedded configurations and the resulting pipelines. Users can create connection and source templates, securely create sources, query API and File Storage sources, monitor connections and jobs, and more.
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### PyAirbyte Fast-Coder MCP
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[The PyAirbyte Fast-Coder MCP](./pyairbyte-fast-coder-mcp.md) is a remote MCP server that provides the ability for data engineers to generate a data pipeline in Python using a single prompt. It is currently designed to work within Cursor, with broader support coming in the near future.
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## Proxy Requests
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### API Sources
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:::warning
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The Airbyte Proxy feature is in alpha, which means it is still in active development and may include backward-incompatible changes. [Share feedback and requests directly with us](mailto:sonar@airbyte.io).
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:::
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@@ -82,6 +78,7 @@ curl -X POST -H 'Content-Type: application/json' \
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Airbyte's Authentication Proxy can be used to authenticate using a Source configured through the Widget.
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The following integrations are currently supported. More will follow shortly:
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- Stripe
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### File Storage Sources
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@@ -89,6 +86,7 @@ The following integrations are currently supported. More will follow shortly:
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Airbyte's File Storage Proxy enables you to submit authenticated requests to file storage sources. It can be used to list or fetch files.
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Here's an example of how to list files:
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```bash
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curl -X GET -H 'Content-Type: application/json' \
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-H 'Authorization: Bearer {AIRBYTE_ACCESS_TOKEN}' \
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@@ -96,6 +94,7 @@ curl -X GET -H 'Content-Type: application/json' \
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```
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Here's an example of how to fetch a file:
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```bash
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curl -X GET -H 'Content-Type: application/octet-stream' \
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-H 'Authorization: Bearer {AIRBYTE_ACCESS_TOKEN}' \
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@@ -106,4 +105,5 @@ curl -X GET -H 'Content-Type: application/octet-stream' \
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For small files, you may omit the `Range` header.
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The following integrations are currently supported. More will follow shortly:
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- S3
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@@ -1,53 +0,0 @@
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---
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products: embedded
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---
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# PyAirbyte Fast-Coder MCP (Deprecated)
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:::warning
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The PyAirbyte Fast-Coder MCP has been deprecated and is no longer actively maintained. If you would like to see continued development on this tool, please let us know by adding feedback on the related GitHub Discussion.
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:::
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The PyAirbyte Fast-Coder MCP is a remote MCP server that provides the ability for data engineers to generate a data pipeline in Python using a single prompt. It is currently designed to work within Cursor, with broader support coming in the near future.
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To add the PyAirbyte MCP open Cursor and navigate to Settings > Tools & Integrations, and tap New MCP Sever. Add the following json snippet. This file tells Cursor which remote MCP servers to connect to and what credentials to pass along.
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Paste the following into your `mcp.json` file:
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```json
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{
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"mcpServers": {
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"pyairbyte-mcp": {
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"url": "https://pyairbyte-mcp-7b7b8566f2ce.herokuapp.com/mcp",
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"env": {
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"OPENAI_API_KEY": "<your-openai-api-key>"
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}
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}
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}
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}
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```
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Make sure to replace `<your-openai-api-key>` with your actual key from the [OpenAI platform](https://platform.openai.com/account/api-keys).
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Save the file. Cursor will automatically detect the MCP server and display **pyairbyte-mcp** as an available MCP tool with a green dot indicating that it has found the available tools.
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Within your Cursor project, start a new chat. In the input box, type the following prompt:
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```bash
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create a data pipeline from source-faker to destination-snowflake
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```
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The MCP server will process your prompt and respond by generating all the necessary Python code to extract data from `faker` and load it into `Snowflake`. We suggest you prefix your source and destination with `source-` and `destination-` to ensure specificity when the MCP server performs a search on the Airbyte Connector registry. Connectors for sources and destinations may have the same name, but different configuration parameters.
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In a few moments, your pipeline will be created, typically in a file called `pyairbyte_pipeline.py`. In addition, the MCP server will generate complete instructions on how to use the server and configure required parameters using a `.env` file that includes environment variables you’ll need to fill in.
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Create a `.env` file and populate it with your source parameters and Snowflake connection details, per generated instructions. For example:
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```env
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AIRBYTE_DESTINATION__SNOWFLAKE__HOST=your_account.snowflakecomputing.com
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AIRBYTE_DESTINATION__SNOWFLAKE__USERNAME=your_user
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AIRBYTE_DESTINATION__SNOWFLAKE__PASSWORD=your_password
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AIRBYTE_DESTINATION__SNOWFLAKE__DATABASE=your_db
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AIRBYTE_DESTINATION__SNOWFLAKE__SCHEMA=your_schema
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AIRBYTE_DESTINATION__SNOWFLAKE__WAREHOUSE=your_warehouse
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```
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@@ -57,11 +57,6 @@ export default {
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id: "pyairbyte-mcp",
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label: "PyAirbyte MCP",
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},
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{
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type: "doc",
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id: "pyairbyte-fast-coder-mcp",
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label: "PyAirbyte Fast-Coder MCP",
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},
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{
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type: "doc",
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id: "connector-builder-mcp",
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