The Privacy-First, Infinitely Extensible Agentic AI Platform for Mobile & Desktop

TealKit turns your phone and computer into a powerful agentic AI platform with autonomous agents, built-in tools, and unlimited extensibility. Write your own tools in JavaScript, Python, PowerShell, or Bash — or connect any MCP server — and let the AI use them autonomously. Provider-independent, fully customizable, and designed for privacy.

English User Guide | Deutsches Handbuch | Privacy Policy

🆕 What's New

• Server Mode — run the TealKit Server as a headless daemon on any always-on Linux device: an NVIDIA Jetson Nano Super, a Mac Mini M4 Pro, a Raspberry Pi, a home-lab VM, or a cheap VPS. Your phone or desktop app connects remotely via a secure API key while all scheduled tasks, automations, and pipelines run 24/7 without the app being open. The server talks to any LLM on a separate GPU-capable machine over the local network — keeps your data home and your compute yours. Ideal for Home Assistant control, server monitoring, daily report generation, or any long-running headless pipeline. A ready-to-deploy, security-hardened Docker image and a one-command setup script will be available to download and install directly on your local device — no registry login required, just download, docker load, and run.
• Embedded (on-device) models — download and run GGUF models directly on your device with zero cloud dependency, and now also fully supported inside the TealKit Server app. Browse the HuggingFace catalog or add any GGUF URL, select CPU / Partial GPU / Full GPU offloading per model, and run inference without an API key or internet connection. Best suited for formatting, translation, and summarisation in Chat Mode; tool calling requires a model trained for function calling and sufficient GPU VRAM to load it fully. Go to Settings → Embedded Models to get started.
• Advanced LLM Parameters — Top-k, top-p, repeat penalty and seed are now configurable in the global LLM Settings dialog (both LLM 1 and LLM 2 tabs) and in the per-task editor. Leave any field blank to use the provider's built-in default. Useful for fine-tuning output diversity and reproducibility — especially with local Ollama models where these parameters have a direct impact on generation quality.
• Chat Mode — A new toggle in Playground and agent settings (Basic tab) that bypasses the system prompt and all tools, forwarding your message directly to the LLM. Perfect for SLMs doing pure text work — translations, formatting, summarisation — where tool overhead adds latency without benefit.
• Agent Chaining (conditional & unconditional) — Chain agents with or without an LLM-evaluated condition. Unconditional chaining always passes the result to the next agent. Conditional chaining evaluates an expression and routes to different follow-up agents depending on the outcome. The triggering agent's output is injected at the [task_result] placeholder in the chained agent's prompt.
• Stop After Tool Call — New option in agent and Playground settings. When enabled the agent runs exactly one tool call, then stops — handing the raw tool output directly as [task_result] to the next chained agent without any further LLM processing. Ideal for data-extraction pipelines where you want unmodified tool output to flow into a downstream agent.

🚀 Core Capabilities

🤖 AI Playground & Flexibility

• Provider Independent: Use leading providers like Google Gemini, OpenAI GPT-5, Anthropic, and Mistral.
• 🇪🇺 European Privacy & GDPR: Data sovereignty matters. TealKit works fully with Mistral AI — a European provider headquartered in France that processes all data within the EU. Ideal for users and organisations where GDPR compliance is non-negotiable. Just enter your Mistral API key and your prompts never leave European infrastructure.
• Small Language Models (SLM): Not every task needs a powerful cloud model. Run lightweight SLMs on your own hardware with Ollama, LM Studio, or any OpenAI-compatible local endpoint — zero cloud costs, zero data sharing. Or use Embedded (on-device) models to download GGUF models directly inside TealKit and run them with no external server at all (Settings → Embedded Models). Mark a model as SLM in LLM Settings to get a compact, action-focused system prompt that forces the model to call tools immediately instead of explaining its plan. For pure text tasks (translation, formatting, summarisation) enable Chat Mode to skip all tools and system prompt overhead entirely — the fastest path from prompt to response for SLMs and embedded models alike. Important: Embedded models are most practical for text tasks; agentic tool calling requires a model explicitly trained for function calling and enough GPU VRAM (dedicated GPU such as Apple Silicon, Snapdragon 8 Elite, or a discrete GPU) to load the full model — without GPU acceleration, inference on a 3 B+ model can take minutes per response.
• Dual-LLM Setup: Configure a secondary LLM (LLM 2) — for example a fast SLM for code tasks — and switch between them directly in the Playground with the LLM 1 / LLM 2 selector. Every model behaves differently; use the Playground to compare prompts across models and find the best fit for each task before automating it.
• Local Intelligence: Support for Ollama models for 100% offline processing.
• Full Customization: Tweak model parameters per task and keep token costs predictable.
• Chat-to-Task: Test ideas in the chat interface before promoting them to automated tasks.
• Auto System Prompt: Select tools and TealKit automatically generates a tailored system prompt via AI — editable before you start.

🛠 Built-in AI Skills

• Document Intelligence: Local RAG using DuckDB. Index PDFs, Word, and Excel files for instant semantic search across your device.
• Digital Office: Deep integration with Gmail and Google Calendar (free) + Google Drive (Pro) + universal IMAP/SMTP support.
• Content & Visualization: Generate files (TXT, PDF, Excel) and create Mermaid diagrams/flowcharts from any data.
• Web Search & Indexing: Perform live searches via SerpApi or DuckDuckGo, and crawl websites for local indexing.
• Remote Management: Manage servers via SSH on all platforms. On Desktop, generate and execute Bash scripts locally (Linux/macOS) or PowerShell scripts (Windows).

⚙️ Agentic Workflows & Automation

• Autonomous Execution: Schedule cron-based tasks that run in the background, even when the app is closed.
• Agent Chaining: Build multi-agent pipelines — with or without conditions. Chain agents unconditionally to always pass results forward, or add an LLM-evaluated condition (e.g., "If X is found, escalate, otherwise archive"). The triggering agent's output is available as [task_result] in the chained agent's prompt. Combine with Stop After Tool Call to pass raw tool output (e.g., SSH command result, web scrape) directly to the next agent without LLM reformatting.
• Multi-Channel Output: Save results to local storage, or send them via Email, Slack, or WhatsApp (with attachments).

💡 Real-World Examples

📱 All Platforms (Mobile + Desktop)

🖥 Desktop Only

🐙 GitHub Integration

🪟 Windows Administration

🔌 Extensibility — Add Any Skill, Connect Any Service

TealKit is an open agentic platform: every capability not built-in can be added as a custom AI skill or by connecting a third-party MCP server — no boilerplate, no backend required.

Your Own AI Skills

Syntax-highlighted code editor: All script libraries (JS, Bash, Python, PowerShell) include a full-screen code editor with syntax highlighting and one-tap expand — making it easy to review, tweak, or copy generated scripts before saving.

Connect to Existing MCP Servers

🆓 Free Forever vs Pro (After Trial)

TealKit includes a full trial. After the trial expires without Pro, core local/manual functionality remains free forever. Pro unlocks automation, remote integrations, advanced outputs, and premium tools.

No TealKit Cloud. Your private data, files, settings, and credentials remain in your device's secure storage. You choose the third-party providers you trust.

💻 Platforms

Platform
Android
Windows
iOS	Coming soon
Linux / Mac	Coming soon

Pro Tip: Unlocking Pro on Mobile also unlocks Pro features for one linked desktop version!

✅ Now Available — Fully Offline with Embedded Models

Run TealKit without any internet connection by loading a GGUF model directly on your device — no API key required. Browse the built-in HuggingFace catalog, paste any direct GGUF download URL, choose CPU / Partial GPU / Full GPU offloading per model, and chat entirely on-device.

Go to Settings → On-device models to download and activate a model. See the Embedded Models section in the User Guide for hardware requirements and recommended models.

📖 Best Practices

See the Best Practices section in the User Guide for tips on reducing token costs, using the script wizards effectively, and choosing the right model for each task.

🖥 Multiple Server Instances for Mixed-Frequency Agents

If you run agents on very different schedules — for example a monitoring agent that fires every few minutes alongside agents that run once a day or weekly — operate them on separate TealKit Server instances (separate Docker containers).

Why this matters:

• Each server instance owns its own DuckDB database. A high-frequency agent writing metrics every few minutes will fragment and lock the database in ways that disrupt low-frequency agents that need long, consistent read windows.
• A short-cycle agent (interval < 10 min) keeps the inference engine and tool runtime warm continuously. Sharing those resources with a heavy daily pipeline causes unpredictable latency spikes and potential queue saturation.
• Isolating instances ensures a crashed or stuck high-frequency agent cannot block a critical daily report or scheduled summary.

Recommended split:

Each Docker container is fully independent — its own data volume, its own DuckDB state, and its own API key registered in the TealKit UI app. Upcoming in the next UI release: a built-in screen to configure and switch between multiple server instances directly from the app — each instance identified by its own API key.

Tip: Both instances can share the same Ollama / LM Studio / embedded-model endpoint if your compute host is separate. Only the TealKit Server process and its storage volume need to be duplicated — not the LLM itself.

Developed by L. Schaffer