List of the Top AI Control Planes for Model Context Protocol (MCP) in 2026

Forest is an operational infrastructure platform built for regulated companies that need a secure way to run humans, AI agents, BPOs, LLMs, suppliers, and workflows together. The platform acts as an operational backend between a company’s data, compliance suppliers, human teams, AI agents, and tools connected through MCP. Forest keeps data inside the customer’s infrastructure while giving teams and agents a shared control plane for business logic, smart actions, workflows, permissions, RBAC, and audit trails. It is designed for regulated environments where agentic operations must remain compliant, auditable, and under control. Forest supports onboarding workflows on top of KYC and KYB providers such as Sumsub, Onfido, Veriff, Persona, and Trulioo. These workflows can combine identity verification, business registry checks, beneficial-owner discovery, document reviews, screening checks, risk scores, jurisdiction logic, and segment-based routing. Routine cases can be triaged by agents, while edge cases can be routed to human reviewers. Every provider call, AI agent step, workflow event, and reviewer decision is recorded at the record level so audit evidence is created as work happens. Forest also helps teams control agents from different sources, including vertical vendors, internal engineering teams, automation tools, and big-tech runtimes. Its implementation approach maps existing databases, providers, and undocumented processes before configuring workflows, then moves selected processes into production with compliance checks and performance audits. By combining operational workflows, MCP access, agent governance, live data connections, permissions, RBAC, audit trails, KYC and KYB orchestration, implementation support, and regulated-process controls, Forest helps companies modernize operations without losing oversight.

Arcade.dev is an innovative platform tailored for the execution of AI tool calls, enabling AI agents to perform real-world tasks like sending emails, messaging, updating systems, or triggering workflows via user-authorized integrations. Acting as a secure authenticated proxy that adheres to the OpenAI API specifications, Arcade.dev facilitates models' access to a variety of external services such as Gmail, Slack, GitHub, Salesforce, and Notion, utilizing both ready-made connectors and customizable tool SDKs while proficiently managing authentication, token handling, and security protocols. Developers benefit from a user-friendly client interface—arcadepy for Python or arcadejs for JavaScript—that streamlines the processes of executing tools and granting authorizations, effectively removing the burden of managing credentials or API intricacies from application logic. The platform boasts impressive versatility, enabling secure deployments across cloud environments, private VPCs, or local setups, and includes a comprehensive control plane for managing tools, users, permissions, and observability. This extensive management framework guarantees that developers can maintain oversight and control, harnessing AI's capabilities to automate a wide range of tasks efficiently while ensuring user safety and compliance throughout the process. Additionally, the focus on user authorization helps foster trust, making it easier to adopt and integrate AI solutions into existing workflows.

Obot serves as an open-source AI infrastructure platform and Model Context Protocol (MCP) gateway, allowing organizations to have a centralized system for discovering, onboarding, managing, securing, and scaling MCP servers that connect large language models and AI agents with various enterprise systems, tools, and data sources. Its features include an MCP gateway, a catalog, an administrative console, and a chat interface that integrates seamlessly with identity providers like Okta, Google, and GitHub, facilitating the implementation of access control, authentication, and governance policies across MCP endpoints to ensure secure and compliant AI interactions. Furthermore, Obot enables IT teams to host both local and remote MCP servers, manage access through a secure gateway, set detailed user permissions, effectively log and audit usage, and generate connection URLs for LLM clients such as Claude Desktop, Cursor, VS Code, or custom agents, thereby enhancing both operational flexibility and security. Additionally, this platform simplifies the integration of AI services, empowering organizations to utilize cutting-edge technologies while upholding strong governance and compliance standards. By streamlining these processes, Obot fosters an environment where innovation can thrive without compromising security or regulatory requirements.

Lunar.dev functions as an all-encompassing platform for AI gateway and API consumption management, specifically crafted to empower engineering teams with a unified interface for monitoring, regulating, securing, and optimizing all interactions with outbound APIs and AI agents. This encompasses the ability to track communications with large language models, employ Model Context Protocol tools, and connect with external services across a variety of distributed applications and workflows. The platform provides immediate visibility into usage trends, latency problems, errors, and associated costs, enabling teams to oversee every interaction involving models, APIs, and agents in real-time. Moreover, it facilitates the implementation of policies such as role-based access control, rate limiting, quotas, and cost management strategies to maintain security and compliance, while preventing excessive use or unexpected charges. By centralizing the oversight of outbound API traffic through features like identity-aware routing, traffic inspection, data redaction, and governance, Lunar.dev significantly enhances operational efficiency for its users. Its MCPX gateway further simplifies the administration of numerous Model Context Protocol servers by integrating them into a single secure endpoint, thereby providing comprehensive observability and permission management for AI tools. In addition, this platform not only alleviates the challenges associated with API management but also substantially increases the capacity of teams to effectively leverage AI technologies, ultimately driving innovation and productivity within organizations.

The Microsoft MCP Gateway functions as a versatile open-source reverse proxy and management interface specifically designed for Model Context Protocol (MCP) servers, enabling scalable and session-aware routing while also providing lifecycle management and centralized control over MCP services, especially in Kubernetes environments. Serving as a control plane, it effectively channels requests from AI agents (MCP clients) to their respective backend MCP servers, ensuring session affinity and managing a variety of tools and endpoints through a unified gateway that emphasizes authorization and observability. Furthermore, it allows teams to deploy, update, and decommission MCP servers and tools using RESTful APIs, which facilitate the registration of tool definitions and resource management, all reinforced by security protocols such as bearer tokens and role-based access control (RBAC). The architecture distinctly differentiates the management of the control plane—which encompasses CRUD operations on adapters, tools, and metadata—from the routing capabilities of the data plane, which accommodates streamable HTTP connections and dynamic tool routing, thereby delivering sophisticated functionalities like session-aware stateful routing. This thoughtful design not only boosts operational efficiency but also cultivates a more secure and robust environment for overseeing AI services, ultimately paving the way for streamlined management and enhanced performance in complex deployments.

Peta acts as a sophisticated control plane for the Model Context Protocol (MCP), facilitating, securing, regulating, and supervising the interactions between AI clients and agents with external resources, data, and APIs. The platform incorporates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and extensive audit logging into a unified solution, allowing organizations to enforce detailed access controls, protect sensitive credentials, and track all interactions performed by AI systems. Central to Peta is Peta Core, which serves as both a secure vault and gateway, responsible for encrypting credentials, generating ephemeral service tokens, ensuring identity verification and policy compliance for each request, managing the lifecycle of the MCP server through lazy loading and auto-recovery, and injecting credentials at runtime without exposing them to agents. Furthermore, the Peta Console enables teams to determine which users or agents can access specific MCP tools within defined environments, set up approval processes, manage tokens, and analyze usage data along with associated costs. This comprehensive strategy not only bolsters security but also promotes effective resource management and accountability across AI operations, ultimately leading to improved operational efficiency and enhanced oversight. By integrating these functionalities, Peta establishes a robust foundation for organizations seeking to optimize their AI-driven initiatives.

Barndoor acts as a comprehensive management layer for data and access, guaranteeing that artificial intelligence systems operate securely alongside enterprise data and infrastructure. It functions as a centralized control hub, managing AI agents and applications, and enabling organizations to establish policies, enforce access controls automatically, and maintain thorough oversight of AI tool operations within their business structures. In contrast to conventional identity-based permissions, Barndoor utilizes context-aware governance, which empowers administrators to control the actions of an AI agent based on specific factors, such as the user supervising the agent, the system being accessed, the type of data involved, and the specific task at hand. This innovative system evaluates each AI request in real time, implementing policies prior to any actions being executed, thus preventing unsafe or unauthorized activities from impacting internal systems or compromising sensitive information. Moreover, this sophisticated approach to governance not only bolsters security and compliance but also cultivates a more reliable AI ecosystem, ultimately benefiting organizations as they navigate the complexities of modern technology. By prioritizing both safety and functionality, Barndoor positions itself as an essential tool for organizations that depend on AI-driven solutions.

Agent Control is an innovative open-source framework that revolutionizes the management of AI agent behavior on a grand scale, establishing a new standard for governance in the field. It tackles the challenges posed by fragmented and hardcoded checks by equipping teams with a cohesive governance layer that applies regulations at every stage, all managed from a single control interface that can be dynamically updated without needing modifications to the agent's core code. Developers can easily identify any function for governance by using the control() decorator, turning critical decision points within an agent into separately regulated control points, each with tailored governance policies. When a function marked with this decorator is executed, Agent Control evaluates the input or output based on the relevant policy, generating responses that can include denying, steering, warning, logging, or allowing the action. Should a denial occur, the SDK raises a ControlViolationError, effectively blocking any potentially harmful actions from being carried out. This clear demarcation of policies from the actual code empowers developers to strategically position control hooks, while governance teams can focus on the specifics of enforcement, promoting a collaborative governance model. The adaptability and strength of Agent Control render it an essential resource for organizations aiming for effective standardization in AI agent governance, and its user-friendly interface further enhances accessibility for developers across various levels of expertise.

Preloop is an open-source control plane tailored for AI agents that can execute real-world tasks, featuring a robust multi-layered security system. This includes an MCP firewall for tool access management, an AI model gateway that promotes cost efficiency, safety, and accountability, along with policy-as-code that emphasizes human oversight, all while ensuring runtime session visibility and maintaining audit trails in a self-hosted environment. As AI agents rapidly gain the ability to deploy code, alter infrastructure, manage financial transactions, access production data, and generate model costs nearly instantaneously, Preloop equips teams with the tools to oversee agent activities, track spending, and identify which actions require human approval. It supports an array of tools such as OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any agents compliant with MCP standards. Moreover, access rules can assess not just tool names but also their arguments and context, utilizing CEL expressions to set specific conditions. Teams are also given the option to start with observability features and gradually implement approval and denial processes without needing SDKs or significant changes to current applications, facilitating a more efficient rollout. This comprehensive strategy not only ensures that organizations retain control over the functionalities of their AI agents but also allows them to adapt to evolving needs and challenges in the AI landscape. Such flexibility is crucial in a rapidly changing technological environment where the implications of AI actions can be profound.

The Cloudflare AI Gateway acts as a sophisticated control system for AI solutions, designed to effortlessly link various models while managing request routing, tracking usage, overseeing billing, and maintaining logs through a unified interface. This innovative platform enhances team capabilities by offering improved visibility and control over their AI solutions, allowing for in-depth analysis of user interactions through comprehensive analytics and logs, as well as effectively managing the scalability of applications with features like caching, rate limiting, request retries, and model fallback options. By leveraging response caching and reducing unnecessary API calls, the AI Gateway significantly cuts costs and decreases latency, enabling rapid requests to be served directly from Cloudflare's cache instead of depending on the original model provider. Furthermore, it enhances reliability through flexible controls that dictate when and how model provider APIs are engaged, influenced by factors such as attributes, fallbacks, latency, cost, and availability. Notably, users can adjust routing rules directly from the dashboard or through API calls without requiring redeployments, thus avoiding any service interruptions and ensuring an efficient operational flow. This capability allows organizations not only to fine-tune their AI app performance but also to retain a high degree of adaptability and control over their processes, ultimately fostering innovation in AI application development.

JetStream Security operates as a governance platform that prioritizes security, enabling businesses to attain thorough visibility, control, and accountability over their AI systems by transforming them from vague, fragmented applications into well-managed and traceable infrastructures. Acting as a centralized control hub, it merges identity management, operational governance, monitoring, and financial oversight into a single, integrated system, which allows enterprises to “track every AI action, link actions to responsible individuals, and ensure that processes remain within authorized boundaries” while enforcing policies in real-time. Additionally, it features agentic identity, which connects human, agentic, and non-human identities to particular actions and access permissions, guaranteeing that every invocation, tool utilization, or workflow can be monitored and regulated in accordance with least-privilege access principles. By ensuring continuous runtime governance, JetStream consistently assesses real AI behavior against established frameworks and employs immutable logging along with real-time monitoring to detect inconsistencies, thereby strengthening security and compliance measures. This comprehensive strategy not only improves accountability but also aids organizations in effectively managing the intricacies associated with AI governance, ultimately fostering a more secure and compliant operational environment. As a result, businesses can confidently optimize their AI usage while adhering to the necessary regulations and best practices.

Singulr serves as a holistic platform tailored for enterprise AI governance and security, offering a unified control structure that supports organizations in discovering, securing, and optimizing their extensive AI deployments. By addressing the growing disparity between the swift adoption of AI technologies and the limitations of governance, it provides unmatched insight into all AI systems employed within the organization, encompassing bespoke applications, integrated AI solutions, publicly available tools, and shadow AI, which frequently bypass security detection. The platform meticulously identifies and inventories AI resources across the enterprise, establishing a dynamic record of agents, models, and services, while assessing their respective risks through comprehensive evaluations of data management, model lineage, vulnerabilities, and compliance standards. Furthermore, Singulr Pulse, the platform’s intelligence layer, analyzes millions of AI systems, assigns risk classifications, and streamlines automated onboarding processes, dramatically reducing approval timelines from weeks to just hours, all while maintaining stringent security protocols. This forward-thinking methodology not only improves the efficiency of AI adoption but also enables organizations to uphold a robust governance structure as they navigate the intricate landscape of AI integration. In doing so, it positions organizations to better respond to the challenges and opportunities presented by the evolving AI landscape.

Bevel functions as a vendor-agnostic control plane integrated with Git, specifically designed for enterprise AI agents, enabling organizations to establish their agents, context, skills, tools, permissions, and identities as proprietary files within their systems, accessible by any agent runtime through the Managed Control Plane (MCP). The context is structured as categorized knowledge nodes, complete with documented provenance that outlines the source, last modification, and verification timestamps, all of which is synthesized into a navigable graph that can be continuously updated for dashboard creation. Skills are defined in clear Markdown formats, allowing process owners to effortlessly read and review modifications, as well as transfer them between various runtimes. Tool manifests detail the available functionalities, while sensitive data is securely encrypted in a vault, managed by access protocols that specify which agents have permission to read particular files or execute certain endpoints. Each agent is allocated a distinctive identity and set of credentials, ensuring traceability of all actions to their origin. This extensive framework not only fortifies security and structure but also fosters transparency and accountability within AI operations, creating a more robust ecosystem for enterprise-level management of AI agents. Furthermore, the system promotes collaborative development, allowing teams to innovate while maintaining control over their AI resources.