Installation & Usage
[01]
Install Package
Using uv or pip
BASH
uv pip install airbyte-agent-gong
[02]
Import
Initialize and use
PYTHON
from airbyte_agent_gong import GongConnector
from airbyte_agent_gong.models import GongAccessKeyAuthenticationAuthConfig
connector = GongConnector(
auth_config=GongAccessKeyAuthenticationAuthConfig(
access_key="<Your Gong API Access Key>",
access_key_secret="<Your Gong API Access Key Secret>"
)
)[03]
Tool
Add tools to your agent
python
@agent.tool_plain # assumes you're using Pydantic AI
@GongConnector.tool_utils
async def gong_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| Users | [List](./REFERENCE.md#users-list), [Get](./REFERENCE.md#users-get), [Search](./REFERENCE.md#users-search) |\n| Calls | [List](./REFERENCE.md#calls-list), [Get](./REFERENCE.md#calls-get), [Search](./REFERENCE.md#calls-search) |\n| Calls Extensive | [List](./REFERENCE.md#calls-extensive-list), [Search](./REFERENCE.md#calls-extensive-search) |\n| Call Audio | [Download](./REFERENCE.md#call-audio-download) |\n| Call Video | [Download](./REFERENCE.md#call-video-download) |\n| Workspaces | [List](./REFERENCE.md#workspaces-list) |\n| Call Transcripts | [List](./REFERENCE.md#call-transcripts-list) |\n| Stats Activity Aggregate | [List](./REFERENCE.md#stats-activity-aggregate-list) |\n| Stats Activity Day By Day | [List](./REFERENCE.md#stats-activity-day-by-day-list) |\n| Stats Interaction | [List](./REFERENCE.md#stats-interaction-list) |\n| Settings Scorecards | [List](./REFERENCE.md#settings-scorecards-list), [Search](./REFERENCE.md#settings-scorecards-search) |\n| Settings Trackers | [List](./REFERENCE.md#settings-trackers-list) |\n| Library Folders | [List](./REFERENCE.md#library-folders-list) |\n| Library Folder Content | [List](./REFERENCE.md#library-folder-content-list) |\n| Coaching | [List](./REFERENCE.md#coaching-list) |\n| Stats Activity Scorecards | [List](./REFERENCE.md#stats-activity-scorecards-list), [Search](./REFERENCE.md#stats-activity-scorecards-search) |
Example Prompts
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List all users in my Gong account - Show me calls from last week - Get the transcript for a recent call - List all workspaces in Gong - Show me the scorecard configurations - What trackers are set up in my account? - Get coaching metrics for a manager - What are the activity stats for our sales team? - Find calls mentioning \{keyword\} this month - Show me calls for rep \{user_id\} in the last 30 days - Which calls had the longest duration last week?
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
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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 Gong connector supports Access Key authentication. You provide a Gong API Access Key and Access Key Secret directly when initializing the connector in open source mode. In hosted mode, credentials are stored securely in Airbyte Cloud using Airbyte client credentials 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?
The Gong connector does not currently support write operations. Actions such as creating users, deleting call recordings, updating scorecards, scheduling meetings, sending feedback, or modifying tracker keywords are not supported. The connector is focused on read operations for sales and revenue data analysis.
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.