airbyte-oss-mcp

airbyte-oss-mcp

Read-only MCP server for self-hosted Airbyte OSS 1.6.x, enabling monitoring of connections, jobs, and health via public and internal APIs. Optionally supports triggering syncs and canceling jobs.

Category
Visit Server

README

Airbyte OSS MCP

Read-only MCP server for self-hosted Airbyte OSS 1.6.x.

Wraps:

  • Public API/api/public/v1 (connections, jobs, health)
  • Internal API/api/v1/jobs/get_without_logs (attempt failure summaries)

Modeled after dagster-mcp (FastMCP + env-based config).

Install (Cursor + uvx)

Prerequisites: uv installed, network access to your Airbyte instance.

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "airbyte": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/NGRThomson/airbyte-oss-mcp.git@main",
        "airbyte-mcp"
      ],
      "env": {
        "AIRBYTE_URL": "https://airbyte.example.com",
        "AIRBYTE_READ_ONLY": "true"
      }
    }
  }
}

Replace AIRBYTE_URL with your instance URL. Default (if unset) is http://localhost:8000.

Pin a tag or commit for slower upgrades:

git+https://github.com/NGRThomson/airbyte-oss-mcp.git@v0.2.0

See examples/cursor-mcp.json for a team install template.

Optional persistent install:

uv tool install --from 'git+https://github.com/NGRThomson/airbyte-oss-mcp.git@main' airbyte-mcp

Local dev

"args": ["--from", "/path/to/airbyte-oss-mcp", "airbyte-mcp"]

Or:

cd airbyte-oss-mcp
uv sync --extra dev
uv run ruff check airbyte_mcp/
uv run pytest
uv run airbyte-mcp

Environment variables

Variable Default Purpose
AIRBYTE_URL http://localhost:8000 Base URL of your Airbyte instance
AIRBYTE_API_TOKEN (empty) Bearer token if public API auth is enabled
AIRBYTE_READ_ONLY true When false, exposes cancel_job and trigger_sync
AIRBYTE_ENVS (empty) JSON map of named envs for multi-instance setups
AIRBYTE_DEFAULT_ENV (empty) Default key when AIRBYTE_ENVS has multiple entries

Multi-env example:

"AIRBYTE_ENVS": "{\"prod\":{\"url\":\"https://airbyte.example.com\"},\"staging\":{\"url\":\"https://airbyte-staging.example.com\"}}",
"AIRBYTE_DEFAULT_ENV": "prod"

Optional bearer token:

"AIRBYTE_API_TOKEN": "<token from Airbyte Settings → Applications>"

Tools

Tool Purpose
get_instance_status Health, connection counts, running/pending/failed job counts
get_active_syncs All running syncs with connection names
list_connections Browse/filter connections
get_connection One connection + recent jobs
list_jobs Recent jobs (filter by connection/status)
get_job Public job metadata
get_job_details Attempt stats + failure summaries
get_job_failure_summary Best starting point for failed syncs
find_duplicate_destination_tables Audit BigQuery tables with multiple active writers

Write tools (cancel_job, trigger_sync) register only when AIRBYTE_READ_ONLY=false.

Smoke test

uv run python -c "
from airbyte_mcp.client import AirbyteClient
c = AirbyteClient('https://airbyte.example.com')
print(c.health())
print('running', len(c.list_jobs(status='running', limit=10)))
"

Notes

  • Always pass orderBy=updatedAt|DESC when listing jobs (default in client) — otherwise Airbyte returns oldest jobs first.
  • Raw job logs are not exposed (public API has no log endpoint); failure summaries come from internal get_without_logs.
  • Internal OSS API: get_job_details and get_job_failure_summary use /api/v1/jobs/get_without_logs, which is not part of the public API and may break on Airbyte upgrades.
  • list_connections / list_jobs paginate automatically when limit exceeds the API page size (100).
  • Runtime data: when pointed at a live instance, tool responses include connection names, job errors, and IDs from your Airbyte workspace — keep MCP read-only in shared Cursor configs if that metadata is sensitive.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured