Compare the Top AI Control Planes that integrate with OpenCode as of September 2026

This a list of AI Control Planes that integrate with OpenCode. Use the filters on the left to add additional filters for products that have integrations with OpenCode. View the products that work with OpenCode in the table below.

What are AI Control Planes for OpenCode?

AI control planes are centralized platforms that help organizations govern, manage, secure, and observe AI models, agents, applications, and infrastructure across enterprise environments. These platforms provide a unified layer for controlling access to AI services, routing model requests, enforcing policies, managing credentials, tracking usage, and monitoring performance across multiple models and AI providers. AI control planes often include capabilities such as model gateways, AI agent governance, guardrails, cost management, observability, security controls, audit logging, rate limiting, and policy enforcement. Many solutions integrate with large language models (LLMs), AI agents, cloud AI services, inference platforms, identity systems, developer tools, and enterprise applications to provide centralized oversight of an organization's AI ecosystem. By consolidating AI management and governance into a common control layer, AI control planes help organizations reduce risk, control costs, improve visibility, and scale AI adoption across teams and applications. Compare and read user reviews of the best AI Control Planes for OpenCode currently available using the table below. This list is updated regularly.

  • 1
    Preloop

    Preloop

    Preloop

    Preloop is the open source AI agent control plane for agents that take real actions. It combines an MCP firewall for tool access, an AI model gateway for cost, safety, and attribution, policy-as-code with human approvals, runtime session observability, and audit trails in a single self-hostable platform. AI agents can deploy code, change infrastructure, move money, touch production data, and burn model spend in seconds, so Preloop helps teams control what agents can do, how much they spend, and which actions require human approval. It works with OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any MCP-compatible agent or managed runtime. Access rules can inspect arguments and context, not just tool names, with CEL expressions for fine-grained conditions. Teams can start with observability, then layer in approvals and deny rules without SDKs or invasive app changes.
    Starting Price: $290 per month
  • 2
    SuperBased

    SuperBased

    SuperBased

    SuperBased is a local-first control plane for AI coding agents that lets developers see, control, and right-size agent activity from one binary running on their own machine. It reads native session data from 40 coding tools without requiring a proxy, SDK rewrite, or special configuration, supporting agents such as Claude Code, Codex, Cursor, GitHub Copilot, OpenCode, Gemini CLI, Kilo Code, Qwen Code, Aider, Devin, and others. The dashboard tracks provider-reported token usage, cache reads and writes, costs, sessions, and projected next-message spend across tools that normally keep their data separate. Developers can also launch more than 20 CLI agents as terminal sessions, monitor several repositories from one screen, attach to a running agent, take over the keyboard, and hand control back when needed. Model routing helps teams match tasks to appropriate models, while egress gates can hold commands before execution so users can stop or redirect costly or risky actions.
    Starting Price: $0.90 per month
  • 3
    Bevel

    Bevel

    Bevel

    Bevel is a vendor-agnostic, Git-backed control plane for enterprise AI agents, where an organization’s agents, context, skills, tools, permissions, and identities are defined as files the company owns in its own infrastructure and served to any agent runtime over MCP. Context is stored as typed knowledge nodes with provenance for every fact, including where it came from, who last changed it, and when it was verified, then compiled into a graph that can be traversed, updated, and used for dashboards. Skills are written as plain Markdown procedures that process owners can read, review in diffs, and port across runtimes. Tool manifests define available capabilities, while secrets stay in a vault and access rules determine which agents may read specific files or call endpoints. Each agent has its own identity, credentials, and scope so actions remain attributable.
  • Previous
  • You're on page 1
  • Next