by airbytehq · MCP Server · ★ 115
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Airbyte Agent SDK Type-safe connector execution framework with blessed connectors and full IDE autocomplete. Overview The Airbyte Agent SDK gives AI agents access to 50+ third-party APIs through strongly typed, well-documented tools. Connectors can run through the Airbyte platform (which manages credentials, rate limiting, and execution) or locally in OSS mode. How to install Documentation Full documentation is available at docs.airbyte.com/ai-agents/about/. Tool integration The SDK ships a hosted tool builder and two decorators for turning connector calls into LLM tools with retry-aware exception translation, output-size guards, and framework-specific error signalling. — preferred for hosted connector agents. Returns , , and callables bound to one connector. Hosted connectors, or local connectors passed an explicit , use outline-only guidance and tell the agent to inspect/read docs before execution; local/offline connectors without a docs provider keep generated YAML-derived rich docs. Pass to make expose only with the legacy rich description. — preferred for typed connectors. Auto-detects the installed framework (pydantic-ai, LangChain, OpenAI Agents, or Fas
| Stars | 115 |
| Forks | 8 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 40.2/100 |
| Open Issues | 5 |
| Last Updated | 2026-04-17 |
| Created | 2025-11-26 |
| Platforms | gemini, mcp, python |
| Est. Tokens | ~1940k |
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airbyte-agent-connectors is 🐙 Drop-in tools that give AI agents reliable, permission-aware access to external systems.. It is categorized as a MCP Server with 115 GitHub stars.
airbyte-agent-connectors is primarily written in Python. It covers topics such as ai, ai-agents, airbyte.
You can find installation instructions and usage details in the airbyte-agent-connectors GitHub repository at github.com/airbytehq/airbyte-agent-connectors. The project has 115 stars and 8 forks, indicating an active community.
The top alternatives to airbyte-agent-connectors on Agent Skills Hub include corpusos, c4-genai-suite, argo. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.