# Voltagent > AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework - **Type:** MCP server - **Install:** `agentstack add mcp-voltagent-voltagent` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [VoltAgent](https://agentstack.voostack.com/s/voltagent) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [VoltAgent](https://github.com/VoltAgent) - **Source:** https://github.com/VoltAgent/voltagent - **Website:** https://voltagent.dev ## Install ```sh agentstack add mcp-voltagent-voltagent ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About AI Agent Engineering Platform English | 繁體中文 | 简体中文 | 日本語 | 한국어 Home Page | Documentation | Examples [](https://github.com/voltagent/voltagent/issues) [](https://github.com/voltagent/voltagent/pulls) [](https://opensource.org/licenses/MIT) [](CODE_OF_CONDUCT.md) [](https://www.npmjs.com/package/@voltagent/core) [](https://www.npmjs.com/package/@voltagent/core) [](https://s.voltagent.dev/discord) [](https://x.com/voltagent_dev) VoltAgent is an end-to-end AI Agent Engineering Platform that consists of two main parts: - **[Open-Source TypeScript Framework](#core-framework)** – Memory, RAG, Guardrails, Tools, MCP, Voice, Workflow, and more. - **[VoltOps Console](#voltops-console)** `Cloud` `Self-Hosted` – Observability, Automation, Deployment, Evals, Guardrails, Prompts, and more. Build agents with full code control and ship them with production-ready visibility and operations. Core TypeScript Framework With the open-source framework, you can build intelligent agents with memory, tools, and multi-step workflows while connecting to any AI provider. Create sophisticated multi-agent systems where specialized agents work together under supervisor coordination. - **[Core Runtime](https://voltagent.dev/docs/agents/overview/) (`@voltagent/core`)**: Define agents with typed roles, tools, memory, and model providers in one place so everything stays organized. - **[Workflow Engine](https://voltagent.dev/docs/workflows/overview/)**: Describe multi-step automations declaratively rather than stitching together custom control flow. - **[Supervisors & Sub-Agents](https://voltagent.dev/docs/agents/sub-agents/)**: Run teams of specialized agents under a supervisor runtime that routes tasks and keeps them in sync. - **[Tool Registry](https://voltagent.dev/docs/agents/tools/) & [MCP](https://voltagent.dev/docs/agents/mcp/)**: Ship Zod-typed tools with lifecycle hooks and cancellation, and connect to [Model Context Protocol](https://modelcontextprotocol.io/) servers without extra glue code. - **[LLM Compatibility](https://voltagent.dev/docs/getting-started/providers-models/)**: Swap between OpenAI, Anthropic, Google, or other providers by changing config, not rewriting agent logic. - **[Memory](https://voltagent.dev/docs/agents/memory/overview/)**: Attach durable memory adapters so agents remember important context across runs. - **[Resumable Streaming](https://voltagent.dev/docs/agents/resumable-streaming/)**: Let clients reconnect to in-flight streams after refresh and continue receiving the same response. - **[Retrieval & RAG](https://voltagent.dev/docs/rag/overview/)**: Plug in retriever agents to pull facts from your data sources and ground responses (RAG) before the model answers. - **[VoltAgent Knowledge Base](https://voltagent.dev/docs/rag/voltagent/)**: Use the managed RAG service for document ingestion, chunking, embeddings, and search. - **[Voice](https://voltagent.dev/docs/agents/voice/)**: Add text-to-speech and speech-to-text capabilities with OpenAI, ElevenLabs, or custom voice providers. - **[Guardrails](https://voltagent.dev/docs/guardrails/overview/)**: Intercept and validate agent input or output at runtime to enforce content policies and safety rules. - **[Evals](https://voltagent.dev/docs/evals/overview/)**: Run agent eval suites alongside your workflows to measure and improve agent behavior. #### MCP Server (@voltagent/mcp-docs-server) You can use the MCP server `@voltagent/mcp-docs-server` to teach your LLM how to use VoltAgent for AI-powered coding assistants like Claude, Cursor, or Windsurf. This allows AI assistants to access VoltAgent documentation, examples, and changelogs directly while you code. 📖 [How to setup MCP docs server](https://voltagent.dev/docs/getting-started/mcp-docs-server/) ## 💛 Sponsors | | | | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | | [TestMu AI (formerly LambdaTest)](https://www.testmuai.com) is an AI-native testing cloud platform built for modern engineering teams. Covering everything from autonomous test creation and fast execution to testing AI agents, chatbots and voice assistants. | ## ⚡ Quick Start Create a new VoltAgent project in seconds using the `create-voltagent-app` CLI tool: ```bash 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`. ```typescript 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: ```bash 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](https://console.voltagent.dev) 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. [](https://github.com/user-attachments/assets/26340c6a-be34-48a5-9006-e822bf6098a7) ### Running Your First Workflow Your new project also includes a powerful workflow engine. The expense approval workflow demonstrates human-in-the-loop automation with suspend/resume capabilities: ```typescript import { createWorkflowChain } from "@voltagent/core"; import { z } from "zod"; export const expenseApprovalWorkflow = createWorkflowChain({ id: "expense-approval", name: "Expense Approval Workflow", purpose: "Process expense reports with manager approval for high amounts", input: z.object({ employeeId: z.string(), amount: z.number(), category: z.string(), description: z.string(), }), result: z.object({ status: z.enum(["approved", "rejected"]), approvedBy: z.string(), finalAmount: z.number(), }), }) // Step 1: Validate expense and check if approval needed .andThen({ id: "check-approval-needed", resumeSchema: z.object({ approved: z.boolean(), managerId: z.string(), comments: z.string().optional(), adjustedAmount: z.number().optional(), }), execute: async ({ data, suspend, resumeData }) => { // If we're resuming with manager's decision if (resumeData) { return { ...data, approved: resumeData.approved, approvedBy: resumeData.managerId, finalAmount: resumeData.adjustedAmount || data.amount, }; } // Check if manager approval is needed (expenses over $500) if (data.amount > 500) { await suspend("Manager approval required", { employeeId: data.employeeId, requestedAmount: data.amount, }); } // Auto-approve small expenses return { ...data, approved: true, approvedBy: "system", finalAmount: data.amount, }; }, }) // Step 2: Process the final decision .andThen({ id: "process-decision", execute: async ({ data }) => { return { status: data.approved ? "approved" : "rejected", approvedBy: data.approvedBy, finalAmount: data.finalAmount, }; }, }); ``` You can test the pre-built `expenseApprovalWorkflow` directly from the VoltOps console: [](https://github.com/user-attachments/assets/3d3ea67b-4ab5-4dc0-932d-cedd92894b18) 1. **Go to the Workflows Page:** After starting your server, go directly to the [Workflows page](https://console.voltagent.dev/workflows). 2. **Select Your Project:** Use the project selector to choose your project (e.g., "my-agent-app"). 3. **Find and Run:** You will see **"Expense Approval Workflow"** listed. Click it, then click the **"Run"** button. 4. **Provide Input:** The workflow expects a JSON object with expense details. Try a small expense for automatic approval: ```json { "employeeId": "EMP-123", "amount": 250, "category": "office-supplies", "description": "New laptop mouse and keyboard" } ``` 5. **View the Results:** After execution, you can inspect the detailed logs for each step and see the final output directly in the console. ## Examples For more examples, visit our [examples repository](https://github.com/VoltAgent/voltagent/tree/main/examples). - **[Airtable Agent](https://voltagent.dev/recipes-and-guides/airtable-agent)** - React to new records and write updates back into Airtable with VoltOps actions. - **[Slack Agent](https://voltagent.dev/recipes-and-guides/slack-agent)** - Respond to channel messages and reply via VoltOps Slack actions. - **[ChatGPT App With VoltAgent](https://voltagent.dev/examples/agents/chatgpt-app)** - Deploy VoltAgent over MCP and connect to ChatGPT Apps. - **[WhatsApp Order Agent](https://voltagent.dev/examples/agents/whatsapp-ai-agent)** - Build a WhatsApp chatbot that handles food orders through natural conversation. ([Source](https://github.com/VoltAgent/voltagent/tree/main/examples/with-whatsapp)) - **[YouTube to Blog Agent](https://voltagent.dev/examples/agents/youtube-blog-agent)** - Convert YouTube videos into Markdown blog posts using a supervisor agent with MCP tools. ([Source](https://github.com/VoltAgent/voltagent/tree/main/examples/with-youtube-to-blog)) - **[AI Ads Generator Agent](https://voltagent.dev/examples/agents/ai-instagram-ad-agent)** - Generate Instagram ads using BrowserBase Stagehand and Google Gemini AI. ([Source](https://github.com/VoltAgent/voltagent/tree/main/examples/with-ad-creator)) - **[AI Recipe Generator Agent](https://voltagent.dev/examples/agents/recipe-generator)** - Create personalized cooking suggestions based on ingredients and preferences. ([Source](https://github.com/VoltAgent/voltagent/tree/main/examples/with-recipe-generator) | [Video](https://youtu.be/KjV1c6AhlfY)) - **[AI Research Assistant Agent](https://voltagent.dev/examples/agents/research-assistant)** - Multi-agent research workflow for generating comprehensive reports. ([Source](https://github.com/VoltAgent/voltagent/tree/main/examples/with-research-assistant) | [Video](https://youtu.be/j6KAUaoZMy4)) VoltOps Console: LLM Observability - Automation - Deployment VoltOps Console is the platform side of VoltAgent, providing observability, automation, and deployment so you can monitor and debug agents in production with real-time execution traces, performance metrics, and visual dashboards. 🎬 [Try Live Demo](https://console.voltagent.dev/demo) 📖 [VoltOps Documentation](https://voltagent.dev/voltops-llm-observability-docs/) 🚀 [VoltOps Platform](https://voltagent.dev/voltops-llm-observability/) ### Observability & Tracing Deep dive into agent execution flow with detailed traces and performance metrics. ### Dashboard Get a comprehensive overview of all your agents, workflows, and system performance metrics. ### Logs Track detailed execution logs for every agent interaction and workflow step. ### Memory Management Inspect and manage agent memory, context, and conversation history. ### Traces Analyze complete execution traces to understand agent behavior and optimize performance. ### Prompt Builder Design, test, and refine prompts directly in the console. ### Deployment Deploy your agents to production with one-click GitHub integration and managed infrastructure. 📖 [VoltOps Deploy Documentation](https://voltagent.dev/docs/deployment/voltops/) ### Triggers & Actions Automate agent workflows with webhooks, schedules, and custom triggers to react to external events. ### Monitoring Monitor agent health, performance metrics, and resource usage across your entire system. ### Guardrails Set up safety boundaries and content filters to ensure agents operate within defined parameters. ### Evals Run evaluation suites to test agent behavior, accuracy, and performance against benchmarks. ### RAG (Knowledge Base) Connect your agents to knowledge sources with built-in retrieval-augmented generation capabilities. ## Learning VoltAgent - **[Start with interactive tutorial](https://voltagent.dev/tutorial/introduction/)** to learn the fundamentals building AI Agents. - **[Documentation](https://voltagent.dev/docs/)**: Dive into guides, concepts, and tutorials. - **[Examples](https://github.com/voltagent/voltagent/tree/main/examples)**: Explore practical implementations. - **[Blog](https://voltagent.dev/blog/)**: Read more about technical insights, and best practices. ## Contribution We welcome contributions! Please refer to the contribution guidelines (link needed if available). Join our [Discord](https://s.voltagent.dev/discord) server for questions and discussions. ## Contributor ♥️ Thanks Big thanks to everyone who's been part of the VoltAgent journey, whether you've built a plugin, opened an issue, dropped a pull request, or just helped someone out on Discord or GitHub Discussions. VoltAgent is a community effort, and it keeps getting better because of people like you. ## License Licensed under the MIT License, Copyright © 2026-present VoltAgent. ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [VoltAgent](https://github.com/VoltAgent) - **Source:** [VoltAgent/voltagent](https://github.com/VoltAgent/voltagent) - **License:** MIT - **Homepage:** https://voltagent.dev Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-voltagent-voltagent - Seller: https://agentstack.voostack.com/s/voltagent - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.