VoltAgent
Build, run, and observe production-oriented AI agents and workflows in TypeScript.
- Source repo
- VoltAgent/voltagent
- Stars
- ★ 11k
- Last updated
- 1d ago
- License
- MIT
- Primary language
- TypeScript
- FA score
- 28/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformChatGPT · OpenAI API · Claude API
- Cost
- Free tier plus a paid hosted plan
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- A TypeScript team exposing a helpful assistant with a weather tool and durable memory over HTTP can organize it with Agent, Memory, honoServer(), and VoltAgent.
- Not a fit if
- Teams that need fully offline operation; VoltOps Console and the managed knowledge base rely on the vendor cloud
- Users wanting no-code agent building; the framework requires writing TypeScript code
- Teams unwilling to configure model-provider API keys and memory storage adapters themselves
- Source review
- 28/100 · Major gaps 8 safety controls not found
What does this agent do, and when should you use it?
VoltAgent is an AI Agent Engineering Platform composed of an open-source TypeScript framework and the VoltOps Console. The framework uses components such as @voltagent/core, Agent, Memory, and VoltAgent to define agents, tools, persistent memory, model providers, and workflows, and can expose an HTTP server through server-hono. It documents supervisor-coordinated sub-agents, declarative multi-step workflows, MCP, RAG, voice, runtime guardrails, and evals. VoltOps Console supplies traces, logs, dashboards, memory management, prompt building, deployment, triggers, monitoring, guardrails, evals, and a knowledge-base capability; the README labels it Cloud and Self-Hosted.
After npm create voltagent-app@latest creates a project, an application can configure an Agent with name, instructions, model, tools, and Memory, then register agents, workflows, honoServer(), and a logger through new VoltAgent. The supplied example uses openai("gpt-4o-mini") from @ai-sdk/openai and persists memory with LibSQLMemoryAdapter({ url: "file:./.voltagent/memory.db" }). npm run dev compiles and runs the service with tsx; the example starts an HTTP server at http://localhost:3141, where the agent can then be tested through VoltOps Console. Workflows can be declared with createWorkflowChain, typed input and result schemas, and .andThen steps; suspend and resumeSchema support a paused flow that resumes after human approval.
- A TypeScript team exposing a helpful assistant with a weather tool and durable memory over HTTP can organize it with Agent, Memory, honoServer(), and VoltAgent.
- A finance or operations team that needs manager review for high-value expenses can model resumable approval with the supplied expenseApprovalWorkflow pattern.
- Developers building a research or task system from specialist roles can use the documented Supervisors & Sub-Agents runtime model.
- An application team that must retrieve facts from its own documents before answering can use retriever agents or VoltAgent Knowledge Base ingestion, chunking, embeddings, and search.
- An engineering team investigating production agent or workflow behavior can inspect traces, logs, performance metrics, and dashboards in VoltOps Console.
- Teams using Claude, Cursor, or Windsurf for coding can expose VoltAgent documentation, examples, and changelogs through @voltagent/mcp-docs-server.
How do you install or deploy this agent?
Run:
npm create voltagent-app@latestThe command guides project setup. The README does not specify a Node.js version, model-provider API-key setup, or VoltOps credentials; using the included openai("gpt-4o-mini") example requires usable OpenAI model access configuration.
How do you use this agent?
From the generated project, run:
npm run devThe starter src/index.ts registers an agent and the expenseApprovalWorkflow from src/workflows/index.ts. The README's startup example exposes http://localhost:3141; use VoltOps Console to select the project, chat with the agent, or run “Expense Approval Workflow” from the Workflows page. A documented small-expense input is {"employeeId":"EMP-123","amount":250,"category":"office-supplies","description":"New laptop mouse and keyboard"}.
What are this agent's strengths and limitations?
- A single @voltagent/core runtime brings agent definitions, tools, memory, models, workflows, and server registration together.
- createWorkflowChain combines Zod input/result schemas, chained steps, and suspend/resumeSchema support for resumable human-in-the-loop flows.
- The README documents configurable provider support across OpenAI, Anthropic, Google, and others alongside MCP, RAG, voice, guardrails, and evals.
- VoltOps Console combines chat testing, execution traces, logs, memory inspection, monitoring, and deployment-oriented platform features.
- The README does not provide a Node.js version, environment-variable names, API-key setup, or full production deployment commands, so adopters must establish those runtime details.
- The example directly uses @ai-sdk/openai, @voltagent/libsql, @voltagent/logger, and @voltagent/server-hono; a real deployment must select and configure the appropriate packages and model provider.
- Although both Cloud and Self-Hosted VoltOps are named, the README gives no pricing, resource requirements, data-retention details, or self-hosting procedure.
- Network access, tool permissions, MCP-server permissions, and guardrail policies are application configuration choices; the README does not define default security boundaries or failure guarantees.
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| VoltAgent This agent | 28 · Major gaps | CLIFreemium | ★ 11k | 1d ago | TypeScript | ChatGPT · OpenAI API · Claude API |
| Kite Agent Framework | 51 · Major gaps | CLIFree + model costs | ★ 11 | 4mo ago | Python | OpenAI API · Claude API |
| Agents Towards Production | Insufficient evidence | Library / SDKFree + model costs | ★ 22k | 4d ago | Jupyter Notebook | — |
| AgentScope 2.0 | 70 · Some gaps | Library / SDKFree + model costs | ★ 35k | 2d ago | Python | OpenAI API · Claude API |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows a security policy (SECURITY.md) and dependency management tools (syncpack), but no concrete implementation or documentation for least privilege, user confirmation, data flow transparency, sensitive data handling, external effects, rollback, or source attribution. Hence these criteria score 0.
Self-consistency: Package names, descriptions, and scripts in README and package.json are mostly consistent, but there are inconsistencies (e.g., @voltagent/mcp-docs-server mentioned in README not explicitly listed in package.json). Dependency availability: package.json lists many dependencies but no lockfile or source verification. Failure messages: No documentation of error handling or user-friendly failure messages.
Audience and scenarios: README clearly targets developers with quick start and multiple examples. Capability boundaries: Documentation lists many features but does not specify limitations. Trigger precision: Workflow example shows triggers but not detailed. Environment fit: Requires Node>=20 and pnpm>=8, but no other environment requirements.
Information architecture: README is well-structured with TOC and links. Install notes: Provides npm create voltagent-app command. Naming stability: Package names and versions exist but no naming conventions. Examples and FAQ: Multiple examples but no FAQ. Known limitations: Not mentioned. License: MIT license clear. Versioning changelog: Changesets configured but no actual changelog. Maintenance responsibility: No clear maintainers or contribution guidelines.
Output usability: Example code shows usage but no output format specification. Marginal value: Rich features but no comparison with other frameworks. Cost benefit: No performance or cost data.
Claim traceability: Feature claims in README not linked to specific code or tests. Cross-source corroboration: No external verification. Fact-inference separation: No clear distinction between facts and inferences in documentation.
- Not found in source: least-privilege scopingGrant only what the task needs: a dedicated account or read-only token, scoped to specific directories and repos.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- Not found in source: data-flow disclosureWatch which external services it contacts (proxy or firewall logs) and keep sensitive data out until you know where it goes.
- Not found in source: sensitive-data handlingUse dedicated, low-privilege, revocable API keys — never production credentials — and keep secrets out of logs.
- Not found in source: dependency securityPin versions and run a dependency audit (npm audit, pip-audit) before installing; prefer running it in a container.
- Not found in source: disclosed external effectsEstablish which external systems it writes to, sends to or changes, and verify with test accounts or repos before production.
- Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
- Not found in source: verifiable attributionInstall from the official repo or registry and check the publisher and URL to avoid look-alike packages.
- No lockfile provided, dependency versions may be unstable.
- Some packages mentioned in README (e.g., @voltagent/mcp-docs-server) are not explicitly listed in package.json, which may cause installation issues.
- No known limitations or security considerations provided, users may underestimate risks.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
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Release notes excerpt
Patch Changes - [#1481](https://github.com/VoltAgent/voltagent/pull/1481) [e481624](https://github.com/VoltAgent/voltagent/commit/e4816249bf0843680ad4200cc33ea077ffcbd116) Thanks [@Arnavkar](https://github.com/Arnavkar)! - fix(core): upgrade the Amazon Bedrock and Google Vertex providers to their AI SDK v6 releases @ai-sdk/amazon-bedrock and @ai-sdk/google-vertex move from 3.x to ^4.0.0. These upgrades move both providers from @ai-sdk/provider-utils@3 to @ai-sdk/provider-utils@4, aligning them with core's AI SDK v6 dependencies. …View on GitHub ↗ -
Release notes excerpt
Minor Changes - [#1423](https://github.com/VoltAgent/voltagent/pull/1423) [316538a](https://github.com/VoltAgent/voltagent/commit/316538a96860ee675931bbbf4f9dd1f6dec3937e) Thanks [@jiangjiang248](https://github.com/jiangjiang248)! - Allow custom workspace sandboxes to receive the original execute_command command and args by disabling toolkit command normalization. Fixes #1422.View on GitHub ↗ -
Release notes excerpt
Patch Changes - [#1350](https://github.com/VoltAgent/voltagent/pull/1350) [80827c3](https://github.com/VoltAgent/voltagent/commit/80827c3f0550fdc3bb608aaef53d71b45551e585) Thanks [@nuthalapativarun](https://github.com/nuthalapativarun)! - Add README documentationView on GitHub ↗