Agentic is a web-based platform designed to empower users to design, deploy, and manage autonomous AI agents without writing code. It offers a drag-and-drop agent builder, seamless API integrations, persistent memory storage, and analytics dashboards. Users can define agent personas, configure custom prompts and event triggers, and link to external services like Slack or CRM systems. The platform also supports scheduling, error handling, and team collaboration, allowing organizations to automate tasks such as data enrichment, email response, report generation, and lead qualification with full visibility and control.
Agentic Core Features
Visual drag-and-drop agent builder
API and webhook integrations
Persistent memory modules
Scheduling and automation
Multi-step workflow orchestration
Real-time monitoring and analytics
Error handling and retry logic
Team collaboration and sharing
Agentic Pro & Cons
The Cons
No direct mobile or desktop app presence indicated
Potential complexity for users unfamiliar with MCP or LLM integration
Pricing details not fully transparent on main site
The Pros
Highly curated tools specifically built for LLM use
Production-ready MCP support with SLAs
Excellent TypeScript developer experience
Stripe usage-based billing for cost efficiency
Fast and reliable MCP gateway leveraging Cloudflare edge network
What is ChatGPT-AUTO - Streamlined Coding Assistant?
ChatGPT AUTO is designed to streamline various coding tasks through automation. Key features include auto-scrolling, automatic continuation of commands, auto-copying results to the clipboard, and optimized layout usage for better screen space utilization. The tool also offers history buttons for viewing and editing previous prompts and results easily. With the auto-close menu and custom prompt editing, users can expect a more efficient and focused coding experience.
ChatGPT-AUTO - Streamlined Coding Assistant Core Features
Ollama Bot is a Node.js-based AI agent designed to run on Discord servers, leveraging the Ollama CLI and local LLM models for generating conversational responses. It establishes a persistent chat context, allowing users to maintain topic continuity over multiple messages. Administrators can define custom prompts, set model parameters, and restrict commands to specific roles. The bot supports multiple LLM models, automatically manages message queues for high throughput, and logs interactions for audit purposes. Installation involves cloning the repository, installing dependencies via npm, and configuring environment variables such as the Discord bot token and Ollama settings. Once deployed, the bot listens for slash commands, forwards queries to the Ollama model, and posts generated replies directly in Discord channels.