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 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
0.1.94
Connector version
0.1.9
SDK commit
e4c7493336bcabf5bea5a761ab7b4edfe2a606a5
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), [Create](./REFERENCE.md#contacts-create), [Get](./REFERENCE.md#contacts-get), [Update](./REFERENCE.md#contacts-update), [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), [Create](./REFERENCE.md#companies-create), [Get](./REFERENCE.md#companies-get), [Update](./REFERENCE.md#companies-update), [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), [Create](./REFERENCE.md#tags-create), [Get](./REFERENCE.md#tags-get) |\n| Notes | [Create](./REFERENCE.md#notes-create) |\n| Segments | [List](./REFERENCE.md#segments-list), [Get](./REFERENCE.md#segments-get) |\n| Internal Articles | [Create](./REFERENCE.md#internal-articles-create) |
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 - Create a new lead contact named 'Jane Smith' with email jane@example.com - Create an internal article titled 'Onboarding Guide' with instructions for new team members - Create a company named 'Acme Corp' with company_id 'acme-001' - Create a tag named 'VIP Customer' - Update the name of contact \{id\} to 'John Updated' - Add a note to contact \{id\} saying 'Followed up on support request' - 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 uses a direct Intercom API Access Token provided via the IntercomAuthConfig model. Hosted mode uses Airbyte Cloud credentials (client ID, client secret, customer name, and optional organization ID) via the AirbyteAuthConfig model, with credentials stored securely in Airbyte Cloud.
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?
Yes, the Intercom connector supports several write operations in addition to reads. Supported write actions include creating and updating contacts, creating notes, creating internal articles, creating and updating companies, and creating tags. Operations like sending messages, deleting contacts/conversations/companies, or assigning conversations are not currently supported.
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.