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voltagent

VoltAgent/voltagent

AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework

GraphCanon updated 3d · GitHub synced 3d

10k stars1.1k forksLast push 1w TypeScript MIT

Decision brief

Voltagent is an AI Agent Engineering Platform built on TypeScript with support for modularity, observability, and easy deployment. It includes tools like a custom logger, memory adapters, and integrations with popular Ll

Good fit when

  • - When you require a TypeScript-based framework that supports integration with various tools including LLM models
  • - If your project emphasizes observability and the need to monitor agent operations closely

Avoid when

  • - Avoid if you prefer languages other than TypeScript for developing AI agents
  • - If ease of deployment and built-in observability features are not critical to your project requirements
Pricing:
freemium - Open-source code available under MIT license but may opt into services with a付费层。请检查官方网站以获取详细信息。

Observed Jul 11, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Active (7d since push)
As of 3d
Provenance
Not a fork · Organization account
As of 3d
Security (OSV)
No MCP manifest
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

npm install voltagent
npm

How it fits your stack(4)

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Similar tools

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Evidence and technical details

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Overview

A versatile platform for developing and running AI agents with a focus on modularity, observability, and ease of deployment. The framework supports integration with various tools including LLM models.

Capability facts

CLI
CLI entrypoint

Source: package.json:bin|scripts · Aug 18, 2026

MCP server
No MCP server detected

Source: repo_scan · Aug 18, 2026

Languages
typescript, javascript

Source: github.language+package.json · Aug 18, 2026

Categories

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README

⚡ Quick Start

Create a new VoltAgent project in seconds using the create-voltagent-app CLI tool:

npm create voltagent-app@latest

This command guides you through setup.

You'll see the starter code in src/index.ts, which now registers both an agent and a comprehensive workflow example found in src/workflows/index.ts.

import { VoltAgent, Agent, Memory } from "@voltagent/core";
import { LibSQLMemoryAdapter } from "@voltagent/libsql";
import { createPinoLogger } from "@voltagent/logger";
import { honoServer } from "@voltagent/server-hono";
import { openai } from "@ai-sdk/openai";
import { expenseApprovalWorkflow } from "./workflows";
import { weatherTool } from "./tools";

// Create a logger instance
const logger = createPinoLogger({
  name: "my-agent-app",
  level: "info",
});

// Optional persistent memory (remove to use default in-memory)
const memory = new Memory({
  storage: new LibSQLMemoryAdapter({ url: "file:./.voltagent/memory.db" }),
});

// A simple, general-purpose agent for the project.
const agent = new Agent({
  name: "my-agent",
  instructions: "A helpful assistant that can check weather and help with various tasks",
  model: openai("gpt-4o-mini"),
  tools: [weatherTool],
  memory,
});

// Initialize VoltAgent with your agent(s) and workflow(s)
new VoltAgent({
  agents: {
    agent,
  },
  workflows: {
    expenseApprovalWorkflow,
  },
  server: honoServer(),
  logger,
});

Afterwards, navigate to your project and run:

npm run dev

When you run the dev command, tsx will compile and run your code. You should see the VoltAgent server startup message in your terminal:

══════════════════════════════════════════════════
VOLTAGENT SERVER STARTED SUCCESSFULLY
══════════════════════════════════════════════════
✓ HTTP Server: http://localhost:3141

Test your agents with VoltOps Console: https://console.voltagent.dev
══════════════════════════════════════════════════

Your agent is now running! To interact with it:

  1. Open the Console: Click the VoltOps LLM Observability Platform link in your terminal output (or copy-paste it into your browser).
  2. Find Your Agent: On the VoltOps LLM Observability Platform page, you should see your agent listed (e.g., "my-agent").
  3. Open Agent Details: Click on your agent's name.
  4. Start Chatting: On the agent detail page, click the chat icon in the bottom right corner to open the chat window.
  5. Send a Message: Type a message like "Hello" and press Enter.

Deployment

Deploy your agents to production with one-click GitHub integration and managed infrastructure.

deployment

📖 VoltOps Deploy Documentation


License

Licensed under the MIT License, Copyright © 2026-present VoltAgent.

For agents

This page has a .md twin and JSON over the API.

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