Cycles vs Preloop: Which is Better in 2026?
A comprehensive comparison of Cycles and Preloop covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Cycles if:
- →You need a broader feature set (7 features vs 6)
- →You need pre-execution gating on cost, risk and tool action or self-hosted with no prompt storage, apache 2.0 licensed
Choose Preloop if:
- →You want more affordable paid plans (from $29/mo)
- →You need mcp firewall with allow, deny and require-approval rules on tool access or ai model gateway with per-agent budgets and cost attribution
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Cycles vs Preloop: At a Glance
Pricing Comparison: Cycles vs Preloop
Understanding the pricing differences between Cycles and Preloop is crucial for making the right choice. Here's how their plans compare side by side.
Cycles Pricing
Preloop Pricing
💡 Pricing takeaway: Both Cycles and Preloop offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Cycles and Preloop stacks up.
What Makes Each Tool Unique
🔵 Unique to Cycles
Features available in Cycles but not in Preloop:
- ✓Pre-execution gating on cost, risk and tool action
- ✓Self-hosted with no prompt storage, Apache 2.0 licensed
- ✓Fail-closed on reserve-time outage
- ✓Published performance: 34ms p99 shared reserve, 891 reserves/sec
- ✓4 SDKs with durable recovery
- ✓Protocol spec plus interactive API and admin API references
- ✓Free blast radius, risk and model cost calculators
🟣 Unique to Preloop
Features available in Preloop but not in Cycles:
- ✓MCP firewall with allow, deny and require-approval rules on tool access
- ✓AI model gateway with per-agent budgets and cost attribution
- ✓Policy-as-code in YAML with CEL expressions
- ✓Human approvals on mobile, watch, Slack, Mattermost or webhook
- ✓One-command discovery and transparent rewrite of existing agent configs
- ✓Runtime session observability and an audit trail for AI Act evidence
Use Case Recommendations
Best for: Cycles
Cycles is a runtime authority layer that stops autonomous agents before they spend too much or take a risky action, rather than reporting on it afterwards. Gating happens pre-execution against cost and risk criteria and against the specific tool action being attempted, which is the difference between a control and an audit log. It is self-hosted with no prompt storage and licensed Apache 2.0, so the enforcement path runs inside your own infrastructure and the code is inspectable — an important property for something sitting in front of every agent action. The published operational numbers are unusually specific for this category: a shared reserve at 34ms p99 for a single client and 891 reserves per second, with 4 SDKs, durable recovery and 12/12 on each, plus a documented fail-closed behaviour on reserve-time outage, which is the correct default for a spend control. Over 21,292 package installs are reported. Documentation covers a protocol spec, interactive API and admin API references, integration guides, security and incident patterns, and there are free calculators for blast radius, risk and Claude-versus-GPT cost. Self-hosting is free; the paid tiers are support and services contracts rather than software licences.
Ideal use cases:
- •Teams or individuals who need pre-execution gating on cost, risk and tool action
- •Teams or individuals who need self-hosted with no prompt storage, apache 2.0 licensed
- •Teams or individuals who need fail-closed on reserve-time outage
- •Teams or individuals who need published performance: 34ms p99 shared reserve, 891 reserves/sec
- •Anyone focused on ai-agents workflows
- •Anyone focused on governance workflows
Best for: Preloop
Preloop is an Apache-2.0 licensed control plane for AI agents, aimed at the governance problem that appears the moment more than one agent is running in an organisation: nobody can see what tools they can reach, what they are spending, or who approved anything. It bundles six capabilities into one self-hostable platform — an MCP firewall that defines allow, deny and require-approval rules on tool access; an AI model gateway that attributes cost and enforces per-agent budgets; policy-as-code written in YAML with CEL expressions; human-in-the-loop approvals delivered to mobile, watch, Slack, Mattermost or a webhook; runtime session observability; and an audit trail. Onboarding is deliberately frictionless: `preloop agents discover` finds compatible agent configurations already on the machine and transparently rewrites them so tool calls route through the MCP firewall and model traffic through the gateway, with no SDK changes and no agent code changes. The named runtimes it rewrites include Claude Code, Codex CLI, Cursor, Gemini CLI, Hermes, OpenClaw, OpenCode and Windsurf. The vendor positions Preloop explicitly as an open-source alternative to AWS Bedrock AgentCore and as a way to build EU AI Act readiness evidence, with dedicated guidance published for that use case. Because the full control plane is Apache 2.0 and self-hostable, the paid tiers sell hosting, team governance and conditional-approval sophistication rather than the core capability.
Ideal use cases:
- •Teams or individuals who need mcp firewall with allow, deny and require-approval rules on tool access
- •Teams or individuals who need ai model gateway with per-agent budgets and cost attribution
- •Teams or individuals who need policy-as-code in yaml with cel expressions
- •Teams or individuals who need human approvals on mobile, watch, slack, mattermost or webhook
- •Anyone focused on mcp workflows
- •Anyone focused on agent-governance workflows
🤖 Other AI Agent Infrastructure Tools to Consider
Cycles and Preloop aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is Cycles better than Preloop?
It depends on your needs. Cycles offers 7 key features including Pre-execution gating on cost, risk and tool action and Self-hosted with no prompt storage, Apache 2.0 licensed, while Preloop provides 6 features including MCP firewall with allow, deny and require-approval rules on tool access and AI model gateway with per-agent budgets and cost attribution. Cycles uses a freemium model with a free tier, while Preloop is open-source with free access available. Choose based on which features and pricing model align with your requirements.
Is Cycles cheaper than Preloop?
Preloop is cheaper, starting at $29/month compared to Cycles's $1,500/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Cycles and Preloop together?
Yes, many users combine Cycles and Preloop in their workflow. Cycles excels at pre-execution gating on cost, risk and tool action, while Preloop shines with mcp firewall with allow, deny and require-approval rules on tool access. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Cycles and Preloop?
While both are ai agent infrastructure tools, Cycles emphasizes pre-execution gating on cost, risk and tool action, whereas Preloop is known for mcp firewall with allow, deny and require-approval rules on tool access. The best choice depends on your specific workflow and feature priorities.
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