Description
️ Tool Name: 🖼
Rivet
Categories: 🔖
Automation and Smart Agents; Programming and Development; Documents and Software Development Toolkits; Integrations and APIs; No-Code Workflows; Testing and Quality Assurance; Repositories and Modeling; Productivity and Scheduling; Data and Analytics.
️ What does this tool offer? ✏
Rivet provides a comprehensive infrastructure for the age of agents, designed to coordinate AI agents, run their environments, automate their tasks, and deploy the applications they build. The platform consists of four core layers: Actors to provide robust and persistent operations for agents;agentOS to provide an isolated computing environment for each agent;Workflows to build multi-step processes that are resumeable after failures and restarts; andDynamic Apps to deploy the applications created by agents.
Rivet offers a composable architecture that brings together the needs of agents into a single stack, including persistent processes, secure code execution, a file system, deployment, real-time communication and streaming, session scripts, memory, isolation, and persistent workflows. These functions are distributed across its various layers; Actors provide persistent operations, memory, and real-time communication, while agentOS provides secure code execution, a file system, isolation, and session scripts, and Workflows handle multi-step persistent processes, while Dynamic Apps handle application deployment.
Rivet supports application development using multiple technologies and frameworks and allows Workers to run on the user’s own infrastructure or via Rivet Cloud. The platform can run locally, within a VPC, in on-premises or air-gapped environments, and can be deployed within existing backend infrastructure. The Enterprise edition also supports the use of Postgres or FoundationDB for persistence, with tiered storage to S3.
The platform also provides monitoring and inspection tools; the Rivet Dashboard allows users to inspect the status of Actors, SQLite data, agentOS sessions, Workflow runs, and Dynamic App instances. Rivet MCP enables users to connect AI clients such as Claude Code, Codex, Cursor, Gemini CLI, and VS Code to the platform to inspect Actors, invoke actions, and open the Actor Inspector directly from the client.
Rivet allows you to get started locally by running ` npm install rivetkit ` and then move to production using Rivet Cloud or self-hosting. On Rivet Cloud, the platform handles the operation of the control plane, while users can run workers on their own infrastructure or use Rivet Compute to run the backend as a container. With the Self-Host option, the open-source control plane can be run as a Rust binary or as a container on the user’s own infrastructure.
What does it actually offer based on user experience? ⭐
- It enables the execution of AI agents within long-running processes that maintain state and identity across requests.
- It provides workflows for executing multi-step tasks with logging, retries, resumption after failures, and restart capabilities.
- agentOS provides an isolated computing environment that agents can use to run code and manage files and sessions.
- The control panel allows you to monitor the status of agents, workflows, sessions, and application versions from a single location.
- Rivet MCP provides access to the Rivet context directly from AI programming clients such as Claude Code, Codex, and Cursor.
- Actors can be developed locally and then deployed to Rivet Cloud or run on-premises according to infrastructure requirements.
Does it include automation? 🤖
Yes, automation is a core feature of Rivet, particularly through Workflows, which allow you to build multi-step processes that can be paused and resumed. Each step can be recorded and re-executed or resumed after a failure; Workflows also support pauses, waiting, branching, and multitasking.
Actors allow for the execution of long-running processes, while agentOS provides a runtime environment for agents, and Dynamic Apps provide a mechanism for running applications built by agents. Thus, automation extends from executing agent tasks to running workflows and then deploying the final output.
Pricing Model: 💰
Freemium / Paid Subscription / Usage-Based Pricing.
Rivet Cloud offers a free plan at $0 per month,along with Hobbyand Team plans starting at $20 and $200 per month, respectively, plus usage fees when limits are exceeded or based on resources consumed. It also offers an Enterprise Edition On-Premise with custom pricing. Rivet also provides a self-hosting option, where the user bears the costs of their own infrastructure and operations.
🆓 Free Plan Details:
| Feature | Details |
|---|---|
| Price | $0 per month |
| Awake Actor Hours | Maximum 100,000 hours per month |
| Compute | Max $5 per month |
| Compute | Up to 1 vCPU |
| Storage | Maximum 5 GB |
| Write Operations | Maximum of 5 million writes per month |
| Read operations | Maximum of 200 million reads per month |
| Data transfer | Maximum 100 GB egress |
| Support | Community support |
Paid Plan Details: 💳
| Plan | Price | Key Features |
|---|---|---|
| Hobby | Starting at $20/month + usage | 400,000 Awake Actor Hours, up to 8 vCPUs, 25 billion reads per month, 50 million writes, 5GB of storage, 1TB of egress, and email support |
| Team | Starting at $200/month + usage | 400,000 Awake Actor Hours, up to 8 vCPUs, 25 billion reads per month, 50 million writes, 5 GB of storage, 1 TB of egress, MFA, and support via Slack |
| Enterprise Edition On-Prem | Custom | Agent Control Plane, FoundationDB, multi-tenant Cloud Layer, SQLite backups, PITR, Forking, ACL, Advanced ClickHouse Analytics, OpenTelemetry, Kubernetes Integrations, Air-gapped and Sovereign Cloud Deployments, plus Dedicated Support and Security |
Pricing for Rivet Cloud:
- Awake Actors: $0.05 per 1,000 Awake Actor Hours.
- State Storage: $0.40 per GB per month.
- Reads: $0.20 per million reads.
- Writes: $1 per million writes.
- Egress: $0.15 per GB.
- Compute: Starting at $0.0000330 per vCPU-second plus $0.0000029 per GiB-second.
How to access the tool: 🧭
| Access Method | Details |
|---|---|
| Web / Cloud | You can create a project and use Rivet Cloud to manage the Control Plane and deploy Actors |
| Locally | You can install RivetKit using ` npm install rivetkit ` and run Actors locally |
| Self-Host | You can run the open-source Rivet Control Plane as a Rust binary or container on your own infrastructure |
| MCP | Rivet can be integrated with clients such as Claude Code, Codex, Cursor, Gemini CLI, and VS Code |
| SDK / Programmatically | RivetKit and APIs are available for building Actors, agentOS, Workflows, and Dynamic Apps |
| Private Infrastructure | Workers can run on Kubernetes, AWS, Railway, Render, VMs, Docker Compose, and more, depending on the deployment method used |
Demo link or official website: 🔗
Rivet’s official website
Official Pricing Page
Official Rivet documentation