Give agents tools for secure, real-time access to fetch, search, write, and sync across every system, with replication, entity mapping, and auth built-in.
About this Connector
GitHub is a platform for version control and collaborative software development using Git. This connector provides access to repositories, branches, commits, issues, pull requests, reviews, comments, releases, organizations, teams, and users for development workflow analysis and project management insights.
CRM
Sales Analytics
Customer Data
Version Information
Package version
0.18.109
Connector version
0.1.15
SDK commit
cb4380e76ac5cbc67b9089f94522be1bbe9f8d73
Support Open Source
Check us out on Github and join the Airbyte community
Installation & Usage
1
Install Package
Using uv or pip
bash
uv pip install airbyte-agent-github
2
Import
Initialize and use
python
from airbyte_agent_github import GithubConnector
from airbyte_agent_github.models import GithubPersonalAccessTokenAuthConfig
connector = GithubConnector(
auth_config=GithubPersonalAccessTokenAuthConfig(
token="<GitHub personal access token (fine-grained or classic)>"
)
)3
Tool
Add tools to your agent
python
@agent.tool_plain # assumes you're using Pydantic AI
@GithubConnector.tool_utils
async def github_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})Supported Entities & Actions
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| Entity | Actions |\n|--------|---------|\n| Repositories | [Get](./REFERENCE.md#repositories-get), [List](./REFERENCE.md#repositories-list), [API Search](./REFERENCE.md#repositories-api_search) |\n| Org Repositories | [List](./REFERENCE.md#org-repositories-list) |\n| Branches | [List](./REFERENCE.md#branches-list), [Get](./REFERENCE.md#branches-get) |\n| Commits | [List](./REFERENCE.md#commits-list), [Get](./REFERENCE.md#commits-get) |\n| Releases | [List](./REFERENCE.md#releases-list), [Get](./REFERENCE.md#releases-get) |\n| Issues | [List](./REFERENCE.md#issues-list), [Get](./REFERENCE.md#issues-get), [API Search](./REFERENCE.md#issues-api_search) |\n| Pull Requests | [List](./REFERENCE.md#pull-requests-list), [Get](./REFERENCE.md#pull-requests-get), [API Search](./REFERENCE.md#pull-requests-api_search) |\n| Reviews | [List](./REFERENCE.md#reviews-list) |\n| Comments | [List](./REFERENCE.md#comments-list), [Get](./REFERENCE.md#comments-get) |\n| Pr Comments | [List](./REFERENCE.md#pr-comments-list), [Get](./REFERENCE.md#pr-comments-get) |\n| Labels | [List](./REFERENCE.md#labels-list), [Get](./REFERENCE.md#labels-get) |\n| Milestones | [List](./REFERENCE.md#milestones-list), [Get](./REFERENCE.md#milestones-get) |\n| Organizations | [Get](./REFERENCE.md#organizations-get), [List](./REFERENCE.md#organizations-list) |\n| Users | [Get](./REFERENCE.md#users-get), [List](./REFERENCE.md#users-list), [API Search](./REFERENCE.md#users-api_search) |\n| Teams | [List](./REFERENCE.md#teams-list), [Get](./REFERENCE.md#teams-get) |\n| Tags | [List](./REFERENCE.md#tags-list), [Get](./REFERENCE.md#tags-get) |\n| Stargazers | [List](./REFERENCE.md#stargazers-list) |\n| Viewer | [Get](./REFERENCE.md#viewer-get) |\n| Viewer Repositories | [List](./REFERENCE.md#viewer-repositories-list) |\n| Projects | [List](./REFERENCE.md#projects-list), [Get](./REFERENCE.md#projects-get) |\n| Project Items | [List](./REFERENCE.md#project-items-list) |\n| File Content | [Get](./REFERENCE.md#file-content-get) |\n| Directory Content | [List](./REFERENCE.md#directory-content-list) |
Example Prompts
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Show me all open issues in my repositories this month - List the top 5 repositories I've starred recently - Analyze the commit trends in my main project over the last quarter - Find all pull requests created in the past two weeks - Search for repositories related to machine learning in my organizations - Compare the number of contributors across my different team projects - Identify the most active branches in my main repository - Get details about the most recent releases in my organization - List all milestones for our current development sprint - Show me insights about pull request review patterns in our team
Why Airbyte for AI Agents?
Built for production AI workloads with enterprise-grade reliability
Agent-Native Design
Structured, LLM-friendly schemas optimized for AI agent consumption with natural language query support.
Secure Authentication
Built-in OAuth 2.0 handling with automatic token refresh. No hard-coded credentials.
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
🦙
LlamaIndex
🤖
CrewAI
⚡
AutoGen
🧠
OpenAI Agents SDK
🔮
Claude Agents SDK
Frequently Asked Questions
Didn't find your answer? Please don't hesitate to reach out.
The GitHub connector supports Personal Access Token authentication (both fine-grained and classic tokens). In hosted mode, credentials are stored securely in Airbyte Cloud and you authenticate using your Airbyte client ID and client secret instead.
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 GitHub connector focuses on read operations only. Write operations such as creating issues, updating pull requests, deleting branches, scheduling reviews, or assigning labels are not supported at this time.
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.
Will there be a platform for agent connectors?
The hosted version with secure credential storage through Airbyte Cloud is already available. See the hosted usage section in the documentation for setup instructions.