CrewAI
Multi-agent automation framework & studio to build and run AI crews
VoltAgent
TypeScript framework for production-ready AI agents with observability
VoltAgent lets developers build, orchestrate, and monitor AI agents using TypeScript, offering memory, workflow orchestration, tool integration, multi-agent supervision, and built-in LLM observability out of the box.
Overview
Overview
VoltAgent is a TypeScript‑first platform that enables teams to create intelligent agents ready for production from day one. It bundles memory adapters, tool registries, and a declarative workflow engine so developers can focus on agent logic rather than infrastructure.
Capabilities
The core runtime supports typed agents, supervisors for coordinating sub‑agents, and provider‑agnostic LLM integration (OpenAI, Anthropic, Google, etc.). Workflows are defined declaratively, allowing human‑in‑the‑loop steps, suspension, and resumption. Built‑in VoltOps provides real‑time execution traces, performance metrics, and OpenTelemetry‑compatible dashboards without external services.
Deployment
Agents run in any Node.js environment, from local servers to serverless platforms. A CLI (npm create voltagent-app@latest) scaffolds projects with example agents, tools, and workflows, and the optional MCP docs server lets LLMs access VoltAgent documentation directly. Monitoring is accessible via the VoltOps console at console.voltagent.dev.
Highlights
Typed core runtime with memory, tools, and workflow engine
Declarative multi-step workflows and supervisor-managed agent teams
Built-in VoltOps observability with real-time traces and OpenTelemetry metrics
Provider-agnostic LLM integration and pluggable memory adapters
Pros
- Full TypeScript type safety across agents and tools
- Production-ready components (memory, workflows, observability) from day one
- Modular architecture supports scaling from single agents to teams
- Observability platform requires no external setup
Considerations
- Requires familiarity with TypeScript and its ecosystem
- Observability UI hosted externally may need internet access
- Limited to Node.js runtime environments
- Custom tooling may need extra configuration for non‑standard LLM providers
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Fit guide
Great for
- Teams building AI assistants that need reliable state and debugging
- Enterprises requiring audit‑ready LLM pipelines
- Developers who prefer declarative workflow definitions over manual control flow
- Projects that already use TypeScript and want seamless LLM integration
Not ideal when
- Python‑centric data science teams without TypeScript expertise
- Simple chatbots where full observability overhead is unnecessary
- Edge deployments with strict binary size constraints
- Environments lacking internet connectivity to VoltOps console
How teams use it
Expense approval automation
Automates expense report validation, routes high‑value requests to managers, and records decisions with audit trails.
AI‑powered coding assistant
Provides contextual code suggestions by retrieving documentation via MCP server and executing tool calls.
Customer support triage
Routes inquiries to specialized sub‑agents, uses memory to retain conversation context, and logs interactions for performance analysis.
Multi‑agent research assistant
Coordinates a team of agents to gather data, summarize findings, and present a cohesive report with real‑time monitoring.
Tech snapshot
TypeScript94%
CSS3%
JavaScript2%
MDX1%
Shell1%
Frequently asked questions
How do I start a new VoltAgent project?
Run `npm create voltagent-app@latest` which scaffolds a TypeScript project with example agents and workflows.
Can I switch LLM providers without changing my agent code?
Yes, configure a different provider (OpenAI, Anthropic, Google, etc.) in the model config; the framework abstracts the provider.
What observability data does VoltOps provide?
Real‑time execution traces, tool usage logs, performance metrics, and OpenTelemetry‑compatible dashboards accessible via the VoltOps console.
How is memory handled across agent runs?
Agents can attach durable memory adapters (e.g., LibSQL) to persist context; the default is an in‑memory store.
Is VoltAgent compatible with serverless deployments?
The core runtime can run in any Node.js environment, including serverless platforms, as long as required dependencies are available.
Project at a glance
Active- Stars
- 4,977
- Watchers
- 4,977
- Forks
- 477
LicenseMIT
Repo age9 months old
Last commit14 hours ago
Primary languageTypeScript
Last synced 2 hours ago