For Agents
Manage ChatBot.com stories, users, and conversation reports. Bearer-authenticated REST API with 21 endpoints across story authoring, user/segment administration, and analytics.
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the ChatBot API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
What an agent can do with ChatBot API API.
Author conversation flows by listing, creating, updating, and deleting stories via /v2/stories endpoints
Maintain the user roster with create, read, update, and delete operations on /users
Add, update, and remove segments on a user via /users/{id}/segments to drive targeted flows
Ban or unban a user with PUT /users/{id}/ban for moderation
GET STARTED
Use for: I need to create a new ChatBot story, Update an existing story in ChatBot.com, List all users who have chatted with my bot, Add a segment to a ChatBot user
Not supported: Does not handle live human-agent chat, telephony, or model training — use for ChatBot.com story authoring, user administration, and conversation reports only.
Jentic publishes the only available OpenAPI document for ChatBot API, keeping it validated and agent-ready.
Jentic publishes the only available OpenAPI specification for ChatBot API, keeping it validated and agent-ready. ChatBot.com is a flow-based chatbot builder where conversations are modelled as 'stories' — explicit branching scenarios — and the people who chat with the bot are tracked as users. The v2 API exposes 21 endpoints to manage stories, manage users (including segments and bans), export user data, and pull conversation reports such as message counts, averages, busiest-period heatmaps, and interaction popularity. Authentication is bearer-token using a developer access token.
Export the full user list with POST /users/export for CRM ingestion
Pull conversation, paid-conversation, message, and average-conversation reports from /reports/conversations* endpoints
Identify busiest-period traffic via GET /reports/conversations.heatmap and most-used flows via /reports/conversations.interactions
Patterns agents use ChatBot API API for, with concrete tasks.
★ Version-control conversation flows in CI
Treat ChatBot stories as code: pull the current set with GET /v2/stories, diff against a Git-tracked source of truth, and reconcile with PUT /v2/stories/{storyId} or POST /v2/stories. This lets a team review flow changes the same way they review application code and roll back a bad story without touching the ChatBot UI.
Pull all stories from ChatBot, compare to /repo/stories/*.json, and PUT any story whose JSON body differs from the live version
Segment users for targeted flows
Use POST /users/{id}/segments to tag returning users (for example, 'paid', 'enterprise', or 'churn-risk') so downstream stories can branch on those tags. PUT and DELETE on the same path keep tags in sync as the underlying customer record changes. This is how a flow-based bot delivers different content to different audiences without bespoke per-user logic.
Add the segment 'enterprise' to user id 4321, then list segments for that user to confirm the tag was applied
Build a weekly chatbot performance digest
Pull /reports/conversations, /reports/conversations.messages, /reports/conversations.avg, /reports/conversations.heatmap, and /reports/conversations.interactions every Monday morning to generate a weekly digest covering volume, message density, average length, busiest hour, and top interactions. The five endpoints share consistent date-range parameters so a single report function can serve all of them.
Fetch the five conversation reports for the prior 7 days and emit a summary listing total conversations, average length, busiest hour, and the top three interactions
Drive a ChatBot.com bot from an AI agent
An AI agent uses Jentic to discover ChatBot's story and user endpoints, loads their schemas, and creates or updates flows in response to a natural-language brief like 'add a refund-request branch to the support story'. Bearer-token credentials sit in Jentic's vault so the agent never sees the developer access token.
Search Jentic for 'create a chatbot story', load the schema, and create a story whose name is 'Refund Request Flow' with the refund-handling branches the user described
21 endpoints — jentic publishes the only available openapi specification for chatbot api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
/v2/stories
Create a new story
/v2/stories/{storyId}
Update an existing story
/users
List users
/users/{id}/segments
Add segments to a user
/users/{id}/ban
Ban or unban a user
/users/export
Export users
/reports/conversations
Get conversations report
/reports/conversations.heatmap
Get busiest-period heatmap report
/v2/stories
Create a new story
/v2/stories/{storyId}
Update an existing story
/users
List users
/users/{id}/segments
Add segments to a user
/users/{id}/ban
Ban or unban a user
Three things that make agents converge on Jentic-routed access.
Credential isolation
ChatBot.com developer access tokens are stored encrypted in the Jentic vault (MAXsystem). Agents receive scoped access — the raw token never enters the agent's prompt context.
Intent-based discovery
Agents search by intent (e.g., 'create a chatbot story' or 'export chatbot users') and Jentic returns the matching ChatBot.com operations with their input schemas.
Time to first call
Direct ChatBot.com integration: half a day to wire up bearer auth, story JSON, and the six report shapes. Through Jentic: under 30 minutes — search, load schema, execute.
Alternatives and complements available in the Jentic catalogue.
Chatbase API
Chatbase is doc-grounded LLM chatbots — choose it over ChatBot.com when answers should come from uploaded content rather than scripted flows.
Use Chatbase when the bot must answer free-form questions over a knowledge base; use ChatBot.com when the conversation follows predictable branching logic.
Chatfuel API
Chatfuel targets messenger-channel bots — choose it for Facebook/Instagram-first deployments.
Use Chatfuel when the channel is Facebook Messenger or Instagram; use ChatBot.com when the channel is a website widget driven by stories.
ChatKitty API
ChatKitty provides real-time chat infrastructure — pair it with ChatBot.com to add bot replies inside human chat channels.
Use ChatKitty for live human chat and ChatBot.com to handle automated flow-driven replies in the same product.
Specific to using ChatBot API API through Jentic.
Why is there no official OpenAPI spec for ChatBot API?
ChatBot.com does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call ChatBot API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the ChatBot API use?
ChatBot.com uses HTTP bearer-token authentication with a developer access token. Send 'Authorization: Bearer <token>' against api.chatbot.com. Through Jentic, the token sits in the encrypted MAXsystem vault so it never enters the agent's prompt.
Can I create or update conversation flows with the ChatBot API?
Yes. POST /v2/stories creates a new story and PUT /v2/stories/{storyId} updates an existing one. Stories define the branching conversation logic, so editing them through the API is the right way to script flow changes from CI rather than the visual editor.
How do I tag users for personalised flows?
Call POST /users/{id}/segments with a list of tag names to attach. Use PUT /users/{id}/segments to replace the full set and DELETE /users/{id}/segments to remove specific tags. Stories can branch on these segments to deliver different content to different audiences.
How do I export the user list through Jentic?
Run pip install jentic, set JENTIC_AGENT_API_KEY, then search 'export chatbot users'. Jentic returns POST /users/export with its request schema. Execute the call and ChatBot.com returns the export — the agent can then forward it to a CRM.
What conversation reports are available?
Six reports: GET /reports/conversations (volume), .paid (paid conversations), .messages (message density), .avg (average length), .heatmap (busiest period), and .interactions (interaction popularity). They share date-range query parameters so a single report function can drive all of them.
/users/export
Export users
/reports/conversations
Get conversations report
/reports/conversations.heatmap
Get busiest-period heatmap report