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
Intercom is a customer messaging platform that enables businesses to communicate with customers through chat, email, and in-app messaging. This connector provides read-only access to core Intercom entities including contacts, conversations, companies, teams, admins, tags, and segments for customer support analytics and insights.
CRM
Sales Analytics
Customer Data
Version Information
Package version
0.1.76
Connector version
0.1.8
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-intercom
2
Import
Initialize and use
python
from airbyte_agent_intercom import IntercomConnector
from airbyte_agent_intercom.models import IntercomAuthConfig
connector = IntercomConnector(
auth_config=IntercomAuthConfig(
access_token="<Your Intercom API Access Token>"
)
)3
Tool
Add tools to your agent
python
@agent.tool_plain # assumes you're using Pydantic AI
@IntercomConnector.tool_utils
async def intercom_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| Contacts | [List](./REFERENCE.md#contacts-list), [Get](./REFERENCE.md#contacts-get), [Search](./REFERENCE.md#contacts-search) |\n| Conversations | [List](./REFERENCE.md#conversations-list), [Get](./REFERENCE.md#conversations-get), [Search](./REFERENCE.md#conversations-search) |\n| Companies | [List](./REFERENCE.md#companies-list), [Get](./REFERENCE.md#companies-get), [Search](./REFERENCE.md#companies-search) |\n| Teams | [List](./REFERENCE.md#teams-list), [Get](./REFERENCE.md#teams-get), [Search](./REFERENCE.md#teams-search) |\n| Admins | [List](./REFERENCE.md#admins-list), [Get](./REFERENCE.md#admins-get) |\n| Tags | [List](./REFERENCE.md#tags-list), [Get](./REFERENCE.md#tags-get) |\n| Segments | [List](./REFERENCE.md#segments-list), [Get](./REFERENCE.md#segments-get) |
Example Prompts
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List all contacts in my Intercom workspace - List all companies in Intercom - What teams are configured in my workspace? - Show me all admins in my Intercom account - List all tags used in Intercom - Show me all customer segments - Show me details for a recent contact - Show me details for a recent company - Show me details for a recent conversation - Show me conversations from the last week - List conversations assigned to team \{team_id\} - Show me open conversations
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 Intercom connector supports two authentication methods: open source mode, where you provide an Intercom API Access Token directly via IntercomAuthConfig; and hosted mode, where credentials are stored securely in Airbyte Cloud and you authenticate using AirbyteAuthConfig with your client ID and 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?
No, the Intercom connector currently supports read-only operations. Write operations such as creating contacts, sending messages, deleting conversations, updating company information, assigning conversations, or creating tags 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.