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Agenite MCP Server

@subeshb1

Basic information

Category

AI & Agents

License

MIT

Transports

stdio

Author

subeshb1

About 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.

Agenite MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Agenite MCP Server tools

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Overview

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

Frequently asked questions

1

What LLM providers are supported?

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

2

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.

3

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.

4

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.

5

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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