ChatFAI is an AI-powered platform that enables users to engage in interactive conversations with AI-generated versions of their favorite fictional characters from various media.
ChatFAI is an AI-powered platform that enables users to engage in interactive conversations with AI-generated versions of their favorite fictional characters from various media. On Nagent, Chatfai is exposed as a fully-configurable ai chatbots integration that any agent can call — 3 actions, and API key authentication. No code is required to wire Chatfai into your workflow — connect it once via the External Integrations panel and reuse it across every agent you build.
Agent builders use Chatfai to automate the kinds of tasks ai chatbots teams previously handled manually. Concrete examples — each one is a single agent step in Nagent — include:
Every action and trigger is paired with a structured input/output schema (visible in the sections below), so when you wire Chatfai into Helix — our agentic agent builder — the editor knows exactly what each step expects and produces. Configure once, deploy anywhere across your Nagent agents.
Every operation an agent can call against Chatfai, with input parameters and output schema. Drop these into any step of an agent built in Helix.
CHATFAI_GET_PUBLIC_CHARACTER_BY_IDTool to retrieve a public character by its ID. Use when you need to fetch details of a single public character by providing its unique ID.
Input parameters
Unique identifier of the public character to retrieve. You can obtain character IDs by searching for characters using CHATFAI_SEARCH_PUBLIC_CHARACTERS.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
CHATFAI_LIST_CHATFAI_CONVERSATIONSTool to list conversations for the authenticated user. Use when you need to retrieve the user's chat conversations or verify authentication status.
Input parameters
Maximum number of conversations to return per page. Use this to control pagination.
Pagination cursor from the previous response's nextCursor field. Use this to fetch the next page of conversations.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
CHATFAI_SEARCH_CHARACTERSTool to search for public characters on ChatFAI by name or keyword. Use when you need to find characters matching a specific search query.
Input parameters
Search query string to find characters by name or keyword. Enter the character name or relevant terms to discover matching public characters.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
No publicly available marketplace agent is found using this tool yet. There are 44 agents privately built on Nagent that already use Chatfai.
Build on Nagent
Connect Chatfai to any Nagent agent in minutes — no API key management, no boilerplate. Just configure and deploy.
The five questions agent builders ask before adopting a new integration.
Open the External Integrations panel inside Nagent (app.nagent.ai/externalIntegration), find Chatfai, and click "Connect Now." You'll authenticate with an API key — Nagent handles credential storage and refresh automatically. Once connected, Chatfai is available to any agent in your workspace.
No. Nagent provides no-code integration for every tool. Once Chatfai is connected, you configure its 3 actions directly in the agent builder UI — no API calls, no boilerplate, no schema management.
Helix — Nagent's agentic agent builder — lets you drop Chatfai steps into any workflow visually. Pick an action (e.g., one of those listed above), fill in the inputs (Helix knows the required vs. optional schema for each parameter), and connect it to upstream/downstream steps. Triggers run as the entry point of an agent, so when a Chatfai event fires, the agent kicks off automatically.
Every Chatfai action and trigger ships with a fully-typed schema — input parameters with name, type, required flag, and description, plus the output payload shape. The schemas are documented in the sections above. Helix uses these schemas to validate your configuration at build time and to type-check the data flowing between steps.
Yes. While Chatfai ships with 3 pre-built ai chatbots actions, you can layer custom logic around them inside Helix — pre/post-processing steps, conditional branches, retries, or stitching Chatfai together with other connected tools. For deeper customization, talk to our team about Nagent's Agentic AI Lab — forward-deployed engineers who build Chatfai-based workflows tailored to your business.