--- title: "voltagent" type: "tool" slug: "voltagent-voltagent" canonical_url: "https://www.graphcanon.com/tools/voltagent-voltagent" github_url: "https://github.com/VoltAgent/voltagent" homepage_url: "https://voltagent.dev" stars: 9972 forks: 1033 primary_language: "TypeScript" license: "MIT" categories: ["developer-tools", "ai-agents"] tags: ["memory", "agents", "tools", "rag", "voice", "ai-agents-framework", "guardrails", "mcp"] updated_at: "2026-07-07T18:34:37.53692+00:00" --- # voltagent > VoltAgent is an end-to-end AI Agent Engineering Platform built on TypeScript. An open-source TypeScript framework to create intelligent agents with memory, tools, multi-step workflows and integration with various AI providers. Includes features like supervisors, workflow engine, and LLM compatibility. ## Facts - Repository: https://github.com/VoltAgent/voltagent - Homepage: https://voltagent.dev - Stars: 9,972 · Forks: 1,033 · Open issues: 70 · Watchers: 90 - Primary language: TypeScript - License: MIT - Last pushed: 2026-07-01T01:24:00+00:00 ## Categories - [Developer Tools](/categories/developer-tools.md) - [AI Agents](/categories/ai-agents.md) ## Tags memory, agents, tools, rag, voice, ai-agents-framework, guardrails, mcp ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [hermes-agent](/tools/nousresearch-hermes-agent.md) - The self-improving AI agent built by Nous Research (★ 210,880) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [JavaGuide](/tools/snailclimb-javaguide.md) - Snailclimb/JavaGuide: 面试 & 后端通用面试指南，覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发 (★ 156,863) - [langflow](/tools/langflow-ai-langflow.md) - Langflow is a powerful platform for building and deploying AI-powered agents and workflows. (★ 151,298) - [dify](/tools/langgenius-dify.md) - Production-ready platform for agentic workflow development (★ 148,070) ## README (excerpt) ```text
voltagent

AI Agent Engineering Platform

English | 繁體中文 | 简体中文 | 日本語 | 한국어

Home Page | Documentation | Examples

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 ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/voltagent-voltagent`](/api/graphcanon/tools/voltagent-voltagent) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_