Agenite MCP Server

@subeshb1

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基本信息

分类

AI 与智能体

许可证

MIT

传输方式

stdio

作者

subeshb1

关于 Agenite MCP Server

🤖 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, Anthropic, AWS Bedrock, and Ollama.

#chat #agent #typescript #ai #mcp #openai #gpt #ai-agents #ai-assistant #aisdk #llm #generative-ai #anthropic #genai #ollama #aws-bedrock #agentic-ai #mcp-server #mcp-client

Agenite MCP Server 配置

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Agenite MCP Server 工具

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概览

What is Agenite?

Agenite is a TypeScript framework for building sophisticated AI agents. It offers a modular, type-safe, and flexible architecture for creating, composing, and controlling AI agents with advanced capabilities like tool integration, multi-agent coordination, and step-based execution.

How to use Agenite?

Install core packages (@agenite/agent, @agenite/tool, @agenite/llm) and at least one provider (e.g., @agenite/openai). Then create an Agent instance with a provider, tools, and instructions, and execute it using agent.execute() or iterate with agent.iterate() for streaming control.

Key features of Agenite

TypeScript-first design with robust type checking
Provider agnostic: supports OpenAI, Anthropic, Bedrock, Ollama
First-class tool integration with JSON Schema validation
Step-based execution using JavaScript generators
Built-in state management with reducers and middleware system
Model Context Protocol (MCP) client for standardized data access

Use cases of Agenite

Building single-purpose assistants with custom tool sets
Creating multi-agent workflows where specialist agents are coordinated
Streaming real-time responses with fine-grained control over LLM calls and tool results
Connecting LLMs to external data sources via MCP servers
Debugging agent execution with middleware like pretty-logger

常见问题

What LLM providers are supported?

The framework supports OpenAI, Anthropic (Claude), AWS Bedrock (Claude and Titan), and local models via Ollama.

How do I define tools for an agent?

Tools are defined using the `Tool` class with a name, description, input schema, and an async `execute` function. Inputs are validated against the schema.

What is the Model Context Protocol (MCP)?

MCP is a standardized protocol for connecting LLMs to data sources (web content, filesystem, databases). Agenite provides an MCP client implementation.

Can I create multi-agent systems?

Yes – agents can be nested. A coordinator agent can delegate tasks to specialist agents, each with their own tools and instructions.

What are the runtime requirements?

Agenite requires Node.js (for npm packages) and TypeScript. Provider packages may need API keys or environment configuration (e.g., AWS credentials for Bedrock).

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