💡 Summary
LLM Tornado is a .NET SDK for building and deploying AI agents and workflows with extensive API integrations.
🎯 Target Audience
🤖 AI Roast: “Powerful, but the setup might scare off the impatient.”
Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress); API keys/tokens handling and storage. Run with least privilege and audit before enabling in production.
LLM Tornado
Build AI agents and workflows in minutes with one toolkit and built-in connectors to 25+ API Providers & Vector Databases.
LLM Tornado is a .NET provider-agnostic SDK that empowers developers to build, orchestrate, and deploy AI agents and workflows. Whether you're building a simple chatbot or an autonomous coding agent, LLM Tornado provides the tools you need with unparalleled integration into the AI ecosystem.
✨ Features
- Use Any Provider: Built-in connectors to: Alibaba, Anthropic, Azure, Blablador, Cohere, DeepInfra, DeepSeek, Google, Groq, Mistral, MoonshotAI, OpenAI, OpenRouter, Perplexity, Requesty, Upstage, Voyage, xAI, Z.ai, and more. Connectors expose all niche/unique features via strongly typed code and are up-to-date with the latest AI development. No dependencies on first-party SDKs. Feature Matrix tracks detailed endpoint support.
- First-class Local Deployments: Run with vLLM, Ollama, or LocalAI with integrated support for request transformations.
- Agents Orchestration: Coordinate specialist agents that can autonomously perform complex tasks with three core concepts:
Orchestrator(graph),Runner(node), andAdvancer(edge). Comes with handoffs, parallel execution, Mermaid export, and builder pattern to keep it simple. - Rapid Development: Write pipelines once, execute with any Provider by changing the model's name. Connect your editor to Context7 or FSKB to accelerate coding with instant access to vectorized documentation.
- Fully Multimodal: Text, images, videos, documents, URLs, and audio inputs/outputs are supported.
- Cutting Edge Protocols:
- MCP: Connect agents to data sources, tools, and workflows via Model Context Protocol with
LlmTornado.Mcp. - A2A: Enable seamless collaboration between AI agents across different platforms with
LlmTornado.A2A. - Skills: Dynamically load folders of instructions, scripts, and resources to improve performance on specialized tasks.
- MCP: Connect agents to data sources, tools, and workflows via Model Context Protocol with
- Vector Databases: Built-in connectors to Chroma, PgVector, Pinecone, Faiss, and QDrant.
- Integrated: Interoperability with Microsoft.Extensions.AI enables plugging Tornado in Semantic Kernel applications with
LlmTornado.Microsoft.Extensions.AI. - Enterprise Ready: Guardrails framework, preview and transform any request before committing to it. Open Telemetry support. Stable APIs.
🔥 News 2026
- 26/01 - Ivy Framework uses
LlmTornado.Agentsto build their AI Components./ocrendpoint is implemented for Mistral./filesendpoint support is extended to all supported providers.
News 2025
- 25/12 - Upstage connector is implemented.
/batchendpoint is implemented for OpenAI, Anthropic, and Google./videosendpoint now supports OpenAI/Sora. - 25/11 - Flowbite Blazor uses LLM Tornado to build their AI Chat WASM component. Requesty connector is implemented.
/tokenizeendpoint is implemented for all Providers supporting the feature. - 25/10 - LLM Tornado is featured in dotInsights by JetBrains. Microsoft uses LLM Tornado in Generative AI for Beginners .NET. Interoperability with Microsoft.Extensions.AI is launched. Skills protocol is implemented.
- 25/09 - Maintainers Matěj Štágl and John Lomba talk about LLM Tornado in .NET AI Community Standup. PgVector and ChromaDb connectors are implemented.
- 25/08 - ProseFlow is built with LLM Tornado. Sciobot – an AI platform for Educators built with LLM Tornado is accepted into Cohere Labs Catalyst Grant Program. A2A protocol is implemented.
- 25/07 - Contributor Shaltiel Shmidman talks about LLM Tornado in Asp.net Community Standup. New connectors to Z.ai, Alibaba, and Blablador are implemented.
- 25/06 - C# delegates as Agent tools system is added, freeing applications from authoring JSON schema manually. MCP protocol is implemented.
- 25/05 - Chat to Responses system is added, allowing usage of
/responsesexclusive models from/chatendpoint. - 25/04 - New connectors to DeepInfra, DeepSeek, and Perplexity are added.
- 25/03 - Assistants are implemented.
- 25/02 - New connectors to OpenRouter, Voyage, and xAI are added.
- 25/01 - Strict JSON mode is implemented, Groq and Mistral connectors are added.
⭐ Samples
- Chat with your documents
- Make multiple-speaker podcasts
- Voice call with AI using your microphone
- Orchestrate Assistants
- Generate images
- [Summarize a video (local file / YouTube)](https://github.com/lofcz/LlmTornado/blob/cfd47f915584728d9a23
Pros
- Supports multiple API providers
- Facilitates rapid development of AI agents
- Offers multimodal input/output capabilities
- Integrates well with existing .NET applications
Cons
- May require familiarity with .NET
- Complexity in orchestrating multiple agents
- Potentially steep learning curve for beginners
- Limited documentation on advanced features
Related Skills
pytorch
S“It's the Swiss Army knife of deep learning, but good luck figuring out which of the 47 installation methods is the one that won't break your system.”
agno
S“It promises to be the Kubernetes for agents, but let's see if developers have the patience to learn yet another orchestration layer.”
nuxt-skills
S“It's essentially a well-organized cheat sheet that turns your AI assistant into a Nuxt framework parrot.”
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author lofcz.
