SmartChatAI MCP. Manage bots, data, and conversations from one command.

Listen up. This server connects your AI agent client—whether it's Claude or Cursor—directly into your entire chatbot infrastructure. You get full control over managing multiple bots and feeding them knowledge bases with PDFs, URLs, or just plain text. Everything runs without you having to leave your terminal.

Managing Your Bots’ Status and Setup

You can figure out exactly what bots you've got running right now by calling list_ai_chatbots. That tool gives you a roster of every active chatbot account managed through the SmartChatAI dashboard. If you need deep details on one specific bot, use get_chatbot_details; it pulls up all the configuration settings for that single instance.

Need to set up a new agent? You can provision one with minimal boilerplate code using create_new_ai_bot, where you just name the bot and give it an initial prompt if you want. For security and identity checks, run get_authenticated_user_profile to grab the profile info tied to your API key.

Feeding Your Bots Knowledge Bases

The bots are only as good as the data you feed 'em. This server lets you train them on diverse sources. If you've got a stack of PDF documents, use add_pdf_to_knowledge_base to index that content immediately. For specific facts or guidelines written out plain text, just pass those strings into add_text_to_knowledge_base so the bot learns off 'em.

When your knowledge comes from an entire website, you don't have to crawl it yourself; use add_website_to_knowledge_base and drop in the URL to index the whole thing. If you need to keep tracking external links on a site before ingesting them all at once, run scrape_domain_links against a domain to scan and index every link found there.

Handling Conversations and Monitoring Activity

You can simulate user conversations by sending an immediate message to any bot using message_ai_chatbot. This sends the prompt and gives you the AI's generated reply right back. To audit performance or extract data for training, you pull the entire chat history with get_bot_chat_history; this tool retrieves the complete record of messages sent and received for any specific chatbot flow.

For monitoring how your bots connect to other systems, run list_configured_webhooks to see a list of all webhooks set up for bot activity tracking. You can also check system integrity anytime you need by running check_api_health, which verifies the SmartChatAI API is up and available to talk with.

A quick rundown on what's happening:

• Getting a Roster: Start by listing all bots using list_ai_chatbots. Then, pick one and use get_chatbot_details for the nitty-gritty setup info. If you need an agent that doesn't exist yet, run create_new_ai_bot to spin up a fresh instance.
• Ingesting Data: Don't forget your sources. PDFs get indexed with add_pdf_to_knowledge_base. Raw text goes through add_text_to_knowledge_base. Whole sites are handled by add_website_to_knowledge_base, or you can pre-scan a domain first using scrape_domain_links.
• Talking to the Bots: To test it out, send a prompt and get an immediate response with message_ai_chatbot. If you need proof of what was said, pull all the transcripts via get_bot_chat_history. The system health check (check_api_health) keeps everything running smoothly.