airbyte-connector-builder-mcp 0.7.1

MCP server for Airbyte connector building operations with AI ownership focus

connector-builder-mcp

Helping robots build Airbyte connectors.

Overview

A Model Context Protocol (MCP) server for Airbyte connector building operations, enabling AI ownership of the complete connector development lifecycle - from manifest validation to automated testing and PR creation.

Key Features

• Manifest Operations: Validate and resolve connector manifests
• Stream Testing: Test connector stream reading capabilities
• Configuration Management: Validate connector configurations
• Test Execution: Run connector tests with proper limits and constraints

MCP Client Configuration

To use with MCP clients like Claude Desktop, add the following configuration:

Stable Version (Latest PyPI Release)

{
  "mcpServers": {
    "connector-builder-mcp--stable": {
      "command": "uvx",
      "args": [
        "airbyte-connector-builder-mcp"
      ]
    }
  }
}

Suggested MCP Server Config

For streamlined onboarding, the below config contains both a PyAirbyte MCP and Connector Builder MCP implementation.

{
  "mcpServers": {
    "airbyte-connector-builder-mcp": {
      "command": "uvx",
      "args": [
        "airbyte-connector-builder-mcp"
      ]
    },
    "airbyte-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "--python=3.11",
        "--from=airbyte@latest",
        "airbyte-mcp"
      ],
      "env": {
        "AIRBYTE_MCP_ENV_FILE": "/Users/{YOUR-USER-ID}/.mcp/airbyte_mcp.env",
        "AIRBYTE_CLOUD_MCP_SAFE_MODE": "1",
        "AIRBYTE_CLOUD_MCP_READ_ONLY": "0"
      }
    }
  }
}

Important:

• Remember to update the AIRBYTE_MCP_ENV_FILE path to your actual path, and to create a new file there at that path. Note that the file can be empty to start.
• For complete setup instructions and environment variable documentation, see the PyAirbyte MCP documentation.

Sample Prompts to Get Started

Below is a simple prompt to get started.

Please create an Airbyte source connector for the Sentry API from scratch using the connector-builder-mcp server tools. Report back to me if your tools do not appear to be working correctly, and don't get creative without permission.

I have a populated a .env file that contains my secrets for the API:

• AUTH_TOKEN
• ORGANIZATION
• PROJECT
• HOSTNAME

The path to the .env is: /path/to/secrets/my-connector-secrets.env. You should pass the absolute path your tools but you should not look inside or try to edit the file.

If testing this process on a connector that already exists, you may also want to append this guidance.

Don't cheat or use any pre-existing connector definitions.

If you want to also publish to Builder, and assuming you've provided your Cloud creds to the PyAirbyte MCP server, you can add:

When this is fully working and tested you can use your other Airbyte MCP server to publish to my Airbyte Cloud workspace.

Running from Source

For information on running from source, see the Contributing Guide.

Complementary MCP Servers

The below MCP servers have been tested to work well with the Connector Builder MCP server and will complement its capabilities.

• Claude Code and Claude Desktop Users: You should only need the PyAirbyte MCP server for most tasks. Specifically, this enables publishing to Airbyte Cloud, running local tests, and validating manifests and configurations.

• Other Clients: Depending on your client, you may want to add the Timer MCP and/or the Playwright MCP for web browsing capabilities.

• PyAirbyte MCP (Recommended): Enables publishing to Airbyte Cloud, running local tests, and syncing data to a local cache for validation.

• Playwright MCP (Optional): Provides web browsing capabilities for researching API documentation.

• Timer MCP (Optional): Adds timekeeping capabilities if your client doesn't have built-in time awareness.

Note: The Connector Builder MCP server manages connector manifest YAML contents via session-based resources, so you do not need a separate file server for manifest storage. However, you may want to enable a Files server in order to store the final manifest contents locally at a path of your choosing.

PyAirbyte MCP

The PyAirbyte MCP Server (powered by PyAirbyte) gives the ability to publish and test connector definitions to your Airbyte Cloud workspace. It also includes tools for more extensive local tests, including syncing data locally to a cache and querying the results with SQL.

{
  "mcpServers": {
    // ... other servers defined here ...
    "airbyte-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "--python=3.11",
        "--from=airbyte@latest",
        "airbyte-mcp"
      ],
      "env": {
        "AIRBYTE_MCP_ENV_FILE": "/Users/{YOUR-USER-ID}/.mcp/airbyte_mcp.env",
        "AIRBYTE_CLOUD_MCP_SAFE_MODE": "1",
        "AIRBYTE_CLOUD_MCP_READ_ONLY": "0"
      }
    }
  }
}

Note:

• Make sure to replace /Users/{YOUR-USER-ID}/.mcp/airbyte_mcp.env with the actual path to your airbyte_mcp.env file.
  • See below for details on the contents of this file.
• For information about the AIRBYTE_CLOUD_MCP_SAFE_MODE and AIRBYTE_CLOUD_MCP_READ_ONLY environment variables, see the PyAirbyte MCP Safety documentation.

Your airbyte_mcp.env file should contain your Airbyte Cloud credentials:

# Airbyte Project Artifacts Directory
AIRBYTE_PROJECT_DIR=/path/to/any/writeable/project-dir

# Airbyte Cloud Credentials (Required for Airbyte Cloud Operations)
AIRBYTE_CLOUD_WORKSPACE_ID=your_workspace_id
AIRBYTE_CLOUD_CLIENT_ID=your_api_key
AIRBYTE_CLOUD_CLIENT_SECRET=your_api_secret

# Optional: Google Creds to Use for GCP GSM (Google Secret Manager):
GCP_GSM_CREDENTIALS_JSON={...inline-json...}

For more detailed setup instructions, please see the PyAirbyte MCP docs.

Files Server MCP

Note: In most cases, you will not need a Files server.

If your agent doesn't already have the ability to read-write files, you can add this:

{
  "mcpServers": {
    // ... other servers defined here ...
    "files-server": {
      "command": "npx",
      "args": [
        "mcp-server-filesystem",
        "/path/to/your/build-artifacts/"
      ]
    }
  }
}

Playwright MCP (Web Browsing)

Playwright is the most common tool used for web browsing, and it doesn't require an API key and it can accomplish most web tasks.

{
  "mcpServers": {
    // ... other servers defined here ...
    "playwright-web-browser": {
      "command": "npx",
      "args": [
          "@playwright/mcp@latest",
          "--headless"
      ],
      "env": {}
    }
  }
}

Timer MCP

If you'd like to time your agent and it does not already include timekeeping ability, you can add this timer tool:

{
  "mcpServers": {
    // ... other servers defined here ...
    "time": {
      "command": "uvx",
      "args": ["mcp-server-time", "--local-timezone", "America/Los_Angeles"]
    }
  }
}

VS Code MCP Extension

For VS Code users with the MCP extension, use the included configuration in .vscode/mcp.json.

Environment Variables

The Connector Builder MCP server supports the following environment variable for configuration:

Session Manifest Path Configuration

• CONNECTOR_BUILDER_MCP_SESSIONS_DIR - Session storage directory
  • Example: /path/to/sessions
  • If set, session-specific subdirectories will be created based on session ID hash
  • Default: {temp_dir}/connector-builder-mcp-sessions/{session_id_hash}/manifest.yaml

Contributing and Testing Guides

• Contributing Guide - Development setup, workflows, and contribution guidelines
• Testing Guide - Comprehensive testing instructions and best practices

Reporting Issues

If you encounter bugs, have feature requests, or need help:

1. Check Existing Issues: Search the GitHub Issues to see if your issue has already been reported
2. Create a New Issue: If your issue is new, open an issue with:
   • A clear, descriptive title
   • Detailed description of the problem or feature request
   • Steps to reproduce (for bugs)
   • Expected vs actual behavior
   • Your environment details (OS, Python version, MCP client)
   • Relevant logs or error messages
3. Community Support: For questions and discussions, you can also reach out through the Airbyte Community Slack

When reporting issues related to specific connectors or the Connector Builder UI itself, please file those in the main Airbyte repository instead.

Troubleshooting

Claude Code Troubleshooting

In Claude Code, you can run /mcp to investigate your MCP Server configuration. This will also print the paths being used for the MCP JSON config.

If for any reason, /mcp does not find your servers, run /doctor to ensure the file can be parsed. If a parsing error is occurring, it will be noted in the /doctor output but not in the /mcp output.