ChatBotKit
Managing multiple chatbots across Slack, Discord, WhatsApp, and your website gets complicated fast. Your Tars AI agent connects to ChatBotKit to list bots, review conversation histories, create new integrations, and manage skillsets, giving your team a unified control layer over your entire conversational AI fleet.
Your AI agent reads ChatBotKit's bot inventory, conversation logs, datasets, and integrations. Managing a multi-channel chatbot deployment becomes a conversation, not a dashboard marathon.
ChatBotKit
Development teams and operations managers use AI agents to manage ChatBotKit deployments, audit bot performance, and ship new integrations without context-switching between dashboards.
Every Monday your QA lead needs to review the previous week's chatbot interactions. Your AI Agent calls ChatBotKit's List Conversations endpoint to pull recent sessions, then retrieves full message threads for flagged conversations using List Conversation Messages. The QA lead gets a summary of conversation volume, identifies problematic interactions, and documents improvement areas, all through a single conversational request instead of clicking through dozens of dashboard pages.
Your team builds a new internal IT help desk bot in ChatBotKit and needs it live on Slack by end of day. Instead of navigating integration settings manually, the project manager tells the Tars agent to create a Slack integration for the bot. The agent calls Create Integration with the bot ID and channel details, confirms the deployment, and reports back with the integration status. The bot is live before the next standup.
Your compliance team requires a quarterly inventory of all AI chatbots deployed across the organization. Your AI Agent calls List Bots to retrieve every bot in ChatBotKit, then calls List Integrations to map each bot to its deployment channels. The compliance officer receives a complete bot inventory with channel mappings, datasets used, and partner account details. A report that took half a day to compile manually is generated in a single conversation.
ChatBotKit
FAQs
The agent calls the Complete Conversation endpoint with a conversation ID and the user's text message. ChatBotKit processes the input through the assigned bot and returns the bot's reply. For real-time applications, you can set the accept header to application/jsonl to enable streaming responses.
Yes. The agent uses the Create Integration endpoint to set up new channel connections. Provide the bot ID, a name for the integration, the channel email or configuration, and optional metadata. The integration becomes active immediately. This works for email, Slack, Discord, and other supported channels.
Tars requires your ChatBotKit API key, which you can generate from the ChatBotKit dashboard. The key grants access to bots, conversations, datasets, skillsets, and integrations within your account. You can list and manage your tokens using the List Tokens endpoint.
No. Tars queries ChatBotKit's API in real time. Conversation histories, bot settings, dataset contents, and integration configurations remain in ChatBotKit's infrastructure. Tars only reads and writes through the API during active interactions.
Yes. The Create Skillset endpoint accepts a name, description, and data object containing skill definitions. Once created, skillsets can be attached to any bot in your ChatBotKit account. Use List Skillsets to review existing skill groups before creating new ones to avoid duplication.
The dashboard and SDK require developers to write code or navigate UI screens. The Tars integration lets non-technical team members manage bots through natural language. Operations, QA, and compliance teams can audit conversations, check deployments, and review datasets without development resources.
Yes. The List Partners endpoint retrieves all partner accounts under your umbrella. This is useful for agencies or enterprises managing multiple ChatBotKit instances. The agent can surface a complete view of sub-accounts, their bots, and deployment status from a single query.
The agent retrieves all datasets configured in your ChatBotKit account via the List Datasets endpoint. Datasets are structured knowledge sources used to train bots, covering product information, FAQs, policies, or any custom content. The agent shows dataset names and pagination details so your team knows what training data is available.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
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