Installation & Usage
[01]
Install Package
Using uv or pip
BASH
uv pip install airbyte-agent-sentry
[02]
Import
Initialize and use
PYTHON
from airbyte_agent_sentry import SentryConnector
from airbyte_agent_sentry.models import SentryAuthConfig
connector = SentryConnector(
auth_config=SentryAuthConfig(
auth_token="<Sentry authentication token. Log into Sentry and create one at Settings > Account > API > Auth Tokens.>"
)
)[03]
Tool
Add tools to your agent
python
@agent.tool_plain # assumes you're using Pydantic AI
@SentryConnector.tool_utils
async def sentry_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})Supported Entities & Actions
Lorem ipsum
Lorem ipsum
| Entity | Actions |\n|--------|---------|\n| Projects | [List](./REFERENCE.md#projects-list), [Get](./REFERENCE.md#projects-get), [Search](./REFERENCE.md#projects-search) |\n| Issues | [List](./REFERENCE.md#issues-list), [Get](./REFERENCE.md#issues-get), [Search](./REFERENCE.md#issues-search) |\n| Events | [List](./REFERENCE.md#events-list), [Get](./REFERENCE.md#events-get), [Search](./REFERENCE.md#events-search) |\n| Releases | [List](./REFERENCE.md#releases-list), [Get](./REFERENCE.md#releases-get), [Search](./REFERENCE.md#releases-search) |\n| Project Detail | [Get](./REFERENCE.md#project-detail-get) |
Example Prompts
Lorem ipsum
List all projects in my Sentry organization - Show me the issues for a specific project - List recent events from a project - Show me all releases for my organization - Get the details of a specific project - What are the most common unresolved issues? - Which projects have the most events? - Show me issues that were first seen this week - Find releases created in the last month
Why Airbyte for AI Agents?
Built for production AI workloads with enterprise-grade reliability
Secure Authentication
Built-in OAuth 2.0 handling with automatic token refresh. No hard-coded credentials.
Agent-Native Design
Heading
Structured, LLM-friendly schemas optimized for AI agent consumption with natural language query support.
Production Ready
Battle-tested connectors with comprehensive error handling, logging, and retry logic.
Open Source
Fully open source under the MIT license. Contribute, customize, and extend freely.
Works with your favorite frameworks
LangChain
CrewAI
LlamaIndex
AutoGen
OpenAI Agents SDK
Claude Agents SDK
Frequently Asked Questions
Didn't find your answer? Please don't hesitate to reach out.
The Sentry connector supports two authentication methods: Open source mode, where you provide a Sentry authentication token directly (generated at Settings > Account > API > Auth Tokens in Sentry), and Hosted mode, where credentials are stored securely in Airbyte Cloud and you authenticate using your Airbyte client ID and client secret.
Can I use this connector with any AI agent framework?
The connector is compatible with any Python-based AI agent framework including LangChain, LlamaIndex, CrewAI, Pydantic AI, and custom implementations.
Does this connector support write operations?
Currently, the Sentry connector focuses on read operations only. Write operations such as creating projects, deleting issues, updating releases, or resolving issues are not supported. Write support may be added in future versions.
How is this different from the Airbyte data connector?
Agent connectors are specifically designed for AI agents and LLM applications. They provide natural language interfaces, optimized response formats, and seamless integration with agent frameworks, unlike traditional ETL-focused connectors.
Get started in minutes with our open-source connector.