🤖 Build powerful AI agents with TypeScript. Agenite makes it easy to create, compose, and control AI agents with first-class support for tools
🤖 Build powerful AI agents with TypeScript. Agenite makes it easy to create, compose, and control AI agents with first-class support for tools, streaming, and multi-agent architectures. Switch seamlessly between providers like OpenAI. The 🤖 agenite mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 3 defined tools rather than through you.
A modern, modular, and type-safe framework for building AI agents using typescript
Agenite is a powerful TypeScript framework designed for building sophisticated AI agents. It provides a modular, type-safe, and flexible architecture that makes it easy to create, compose, and control AI agents with advanced capabilities.
The server ships on npm as @agenite/agent, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Everything the assistant can do here goes through one of these:
Agents — Agents are the central building blocks in Agenite. An agent: - Orchestrates interactions between LLMs and tools - Manages conversation state andTools — Tools extend agent capabilities by providing specific functionalities: - Strong type safety with TypeScript - JSON Schema validation for inputs -Providers — Currently supported LLM providers: - OpenAI API (GPT models) - Anthropic API (Claude models) - AWS Bedrock (Claude, Titan models) - Local models viaAmong the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. 🤖 Agenite's toolset — Agents, Tools, Providers — is a fair guide to whether it matches your workflow. It is maintained by subeshb1; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against 🤖 Agenite's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Agents | Agents are the central building blocks in Agenite. An agent: - Orchestrates interactions between LLMs and tools - Manages conversation state and context - Handles tool execution and results - Supports nested execution fo |
| Tools | Tools extend agent capabilities by providing specific functionalities: - Strong type safety with TypeScript - JSON Schema validation for inputs - Flexible error handling - Easy API integration |
| Providers | Currently supported LLM providers: - OpenAI API (GPT models) - Anthropic API (Claude models) - AWS Bedrock (Claude, Titan models) - Local models via Ollama |
{
"mcpServers": {
"agenite": {
"command": "npx",
"args": ["-y", "@agenite/agent"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.