Discover +72 AI Chat apps & tools

Pros: Connects to diverse Kubernetes clusters.. Integrates multiple built-in and private AI models.. Offers 49 multi-cluster MCP tools.. Aids beginners with AI-assisted functions..

Cons: Requires manual change of default credentials.. Users must configure external private AI models..

Pros: Connects to multiple LLM providers and proxies.. Integrates external MCP server tools.. Features a proot-based Linux Workspace.. Supports multimodal input and Markdown rendering..

Cons: Requires managing separate API keys for providers.. RikkaWeb server needs Java 17+ runtime.. Agent tools depend on external MCP servers.. Main Rikkahub lacks direct device-level tool exposure..

Pros: Enables interactive HTML UIs in AI chatbots.. Supports OAuth for secure tool protection.. UIs run securely in sandboxed iframes.. Provides SDK and Agent Skills for development..

Cons: Requires separate JSON-RPC protocol for UI communication.. Needs explicit user consent for UI-initiated tool calls..

Pros: Connects to many AI models and providers.. Offers extensive built-in agent tools.. Supports multi-language Code Interpreter.. Provides granular access control..

Cons: Requires manual setup of external services.. SSE transport not recommended for production.. Production deployments need secure JWT secrets.. MCP servers require user OAuth or API keys..

Pros: Connects AI to personal WhatsApp accounts.. Supports multiple AI clients like Claude.. Exposes specific tools for chat management.. Hybrid Go and Python architecture..

Cons: Requires a personal WhatsApp account.. No built-in authentication for the MCP server.. Requires manual QR code scanning for initial setup.. Needs external reverse proxy for secure binding..

Pros: Open-source, local-first AI agent desktop client.. Connects to many cloud and local AI models.. Supports Model Context Protocol (MCP).. Includes callable Skills and inMemory services..

Cons: Not an MCP server, only a client.. Direct API key use is limited to prototyping.. Requires manual API key and MCP service configuration..

Pros: Exposes granular Nextcloud operations via 100+ MCP tools. In-browser AI actions through a native Nextcloud application. Docker image plus one-command Hetzner provisioning with Traefik and CrowdSec.

Cons: Requires self-hosting and operational familiarity for deployment. Generated factual outputs depend on the connected assistant's accuracy. Compatibility listed only through Nextcloud version 34.

Pros: Cross-agent memory sharing prevents repeated context explanations. Graph-based retrieval removes the need for an external vector database. MCP support connects directly to MCP-compatible clients. Source ingestion imports docs, archives, and agent transcripts.

Cons: CLI deployment requires a Node.js environment. Self-hosting requires ongoing infrastructure maintenance. Relies on MCP-compatible agents for full integration.

Pros: Local-first storage using SQLite for chat and character memory. Model Context Protocol support for external tool integration. Built-in Live2D rendering with eye-tracking and motion triggers. Multiple TTS/STT backends, including Whisper and Edge TTS.

Cons: Source builds require Node.js v18+ and Rust, increasing setup work. Customization expects web development skills for MODs and scripts. Generated responses depend on chosen language backend; verify accuracy.