LLMTornado
The .NET library to build AI agents with 30+ built-in connectors.
What is LLMTornado?
LLMTornado is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to .net library to build ai agents with 30+ built-in connectors.
The .NET library to build AI agents with 30+ built-in connectors.
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- The .NET library to build AI agents with 30+ built-in connec
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx llmtornadoConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use LLMTornado
LLM Tornado is a provider-agnostic .NET SDK for building AI agents and workflows with built-in connectors to more than 30 LLM providers and vector databases including Anthropic, OpenAI, Google, Mistral, Groq, DeepSeek, and others. It includes NuGet packages for core inference, an agentic orchestration framework (LlmTornado.Agents), MCP protocol support (LlmTornado.Mcp), Agent-to-Agent protocol (LlmTornado.A2A), and Semantic Kernel interoperability. .NET developers use it to write provider-agnostic AI pipelines once and switch between models by changing a single string, without depending on first-party SDKs.
Prerequisites
- .NET 8 or later SDK installed
- A NuGet-compatible project (console app, ASP.NET, Blazor, etc.)
- API keys for the LLM providers you intend to use (e.g., Anthropic, OpenAI, Google)
- Optional: a vector database (Chroma, Pinecone, PgVector, Qdrant, or Faiss) for RAG workflows
- An MCP client if using LlmTornado.Mcp for MCP server integration
Install the core NuGet package
Add LlmTornado to your .NET project. This is the only package required for basic inference across all supported providers.
dotnet add package LlmTornadoInstall optional addon packages
Add extra packages depending on your use case: Agents for orchestration, Mcp for Model Context Protocol, A2A for agent-to-agent communication, or Microsoft.Extensions.AI for Semantic Kernel interoperability.
dotnet add package LlmTornado.Agents
dotnet add package LlmTornado.Mcp
dotnet add package LlmTornado.A2A
dotnet add package LlmTornado.Microsoft.Extensions.AICreate a TornadoApi instance with your provider keys
Instantiate the API client with one or more provider credentials. LLM Tornado automatically selects the correct key based on the model you request.
using LlmTornado;
using LlmTornado.Chat.Models;
TornadoApi api = new TornadoApi([
new (LLmProviders.Anthropic, "YOUR_ANTHROPIC_KEY"),
new (LLmProviders.OpenAi, "YOUR_OPENAI_KEY"),
new (LLmProviders.Google, "YOUR_GOOGLE_KEY")
]);Run your first inference
Create a conversation, append a user message, and call GetResponse. Switch providers by changing the ChatModel argument — no other code changes needed.
string? response = await api.Chat
.CreateConversation(ChatModel.Anthropic.Claude37.Sonnet)
.AppendSystemMessage("You are a helpful assistant.")
.AppendUserInput("Summarize the key benefits of provider-agnostic AI SDKs.")
.GetResponse();
Console.WriteLine(response);Add MCP support (optional)
Reference LlmTornado.Mcp and connect your agent to any MCP server to give it access to external tools and data sources.
dotnet add package LlmTornado.McpLLMTornado Examples
Client configuration
Minimal C# program showing multi-provider setup and a single inference call. Replace placeholder keys with real values from each provider's console.
{
"note": "LLM Tornado is a .NET library, not an MCP server itself. Configure via code:",
"nuget": "LlmTornado",
"quickstart": "dotnet add package LlmTornado && dotnet add package LlmTornado.Agents"
}Prompts to try
Capability ideas and tasks you can implement with LLM Tornado in your .NET application.
- Build an agent that routes requests to the cheapest available provider based on token cost
- Orchestrate a researcher agent and a writer agent using LlmTornado.Agents handoffs
- Connect your agent to an MCP server (e.g., filesystem, database) via LlmTornado.Mcp
- Generate embeddings with Voyage or OpenAI and store them in PgVector or Qdrant
- Create a multi-speaker podcast script from a document using the audio synthesis APIsTroubleshooting LLMTornado
API call fails with 'AuthenticationError' for a specific provider
Verify that the API key string passed to TornadoApi for that provider is correct and active. Each provider key is independent — an invalid OpenAI key will not affect Anthropic calls.
Model name is not recognized
Use the strongly-typed ChatModel constants (e.g., ChatModel.Anthropic.Claude37.Sonnet) to avoid typos, or pass the model string exactly as the provider documents it. LLM Tornado resolves the provider automatically from the model name.
LlmTornado.Agents package not found
Ensure you are targeting .NET 8 or later. Run 'dotnet restore' after adding the package reference, and confirm your NuGet feed includes nuget.org.
Frequently Asked Questions about LLMTornado
What is LLMTornado?
LLMTornado is a Model Context Protocol (MCP) server that .net library to build ai agents with 30+ built-in connectors. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install LLMTornado?
Follow the installation instructions on the LLMTornado GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with LLMTornado?
LLMTornado works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is LLMTornado free to use?
Yes, LLMTornado is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Browse More Coding Agents MCP Servers
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Set Up LLMTornado in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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