Top Lunar.dev Alternatives

BAND develops comprehensive interaction frameworks tailored for large-scale applications of distributed AI agents. This platform enables real-time, collaborative communication between agents and humans while integrating a runtime control plane that maintains policy adherence, establishes authority boundaries, and guarantees transparency across varied systems. Moreover, BAND supports developers, engineering teams, and leaders overseeing enterprise platforms that manage multi-agent ecosystems across internal frameworks, SaaS offerings, and collaborative environments with partners. This robust support not only improves operational efficiency but also stimulates innovation within intricate organizational frameworks, ultimately driving progress and adaptability in a rapidly evolving technological landscape.

agentgateway is a comprehensive AI gateway platform that unifies security, connectivity, and observability for enterprise AI ecosystems. It provides a single control point for managing LLM consumption, AI inference, and agentic workflows. Built for emerging standards like MCP and agent-to-agent communication, agentgateway supports use cases beyond the reach of traditional API gateways. The platform secures LLM access by protecting provider keys, preventing prompt abuse, and controlling costs. It offers an inference gateway that optimizes model serving, prioritizes critical workloads, and improves performance. agentgateway also delivers a dedicated agent gateway to manage tool servers, registries, and permissions at scale. Organizations gain full visibility into every agent and tool interaction. OpenTelemetry integration enables deep observability and evaluation of AI behavior. Hosted by the Linux Foundation, agentgateway is committed to open, interoperable AI infrastructure. It is trusted by leading enterprises across industries. The platform enables responsible AI adoption with strong governance and control. agentgateway future-proofs enterprise infrastructure for the next generation of AI systems.

MuleSoft is an enterprise platform built to make AI agents, APIs, applications, data, and systems easier to connect, govern, secure, and orchestrate from one centralized control plane. It helps organizations move into the agentic era by giving IT teams the tools to manage AI-driven interactions without losing visibility or control. MuleSoft Agent Fabric enables companies to govern and coordinate AI agents across different platforms, supporting compliance, performance improvement, and stronger business value. MuleSoft Omni Gateway helps teams oversee every interaction between APIs, agents, models, and enterprise systems across multiple environments. The platform also includes Trusted Agent Identity, which helps agents securely act on behalf of users when interacting with downstream services. With MuleSoft Agent Scanners, organizations can discover AI agents across platforms such as Amazon Bedrock and Google Vertex AI, then register them in a governed system to reduce shadow AI. MuleSoft Agent Registry centralizes agents, tools, and digital assets, while Agent Broker supports complex process orchestration through defined rules and dynamic task routing. The platform also supports multi-agent collaboration, API governance, monitoring, partner management, intelligent document processing, and hundreds of prebuilt connectors. Development teams can build APIs, integrations, and automations using natural language, clicks, or code through tools such as MuleSoft Vibes, MuleSoft Your Way, and Anypoint Code Builder. MuleSoft also supports customer success through professional services, training, partners, documentation, tutorials, demos, and community resources. MuleSoft is built for organizations that want to accelerate AI adoption, modernize integration, improve governance, and confidently scale agentic workflows across the enterprise.

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.

Willow is an all-encompassing enterprise platform crafted for the management of AI agents, tools, MCP servers, skills, and plugins. It enables seamless integration of a multitude of agents, including Claude, ChatGPT, Cursor, Codex, Gemini, n8n, and tailored agents into both internal systems and SaaS solutions like Jira, GitHub, Slack, and various databases through an MCP gateway. Each agent is equipped with a unique human-linked identity, designated permissions, and a detailed audit trail to ensure accountability. Security teams are responsible for developing policies, while employees can independently access approved connectors, skills, and plugins as required. Among its many features are shadow AI discovery, redaction of PII, prompt-injection inspection, permissions at both app and action levels, alongside integrations for SSO, SCIM, and RBAC with platforms such as Okta, Entra ID, and JumpCloud. Furthermore, Willow provides functionalities for SIEM export, tracking of tokens and costs, and operates background agents to boost overall performance. The platform is offered in various deployment options, including SaaS, dedicated cloud, or on-premises deployment within a customer’s VPC. With a SOC 2 Type II attestation and adherence to GDPR regulations, Willow has achieved significant adoption and is currently in active use by leading companies like Wix, Innovid, and Riskified, ensuring it aligns with stringent industry benchmarks. This combination of versatility and a strong focus on security positions Willow as an excellent option for organizations aiming to responsibly leverage AI technologies. Ultimately, its comprehensive features and commitment to compliance empower businesses to navigate the complexities of AI integration with confidence.

Solo Enterprise delivers an all-encompassing cloud-native solution for application networking and connectivity that allows organizations to securely link, expand, oversee, and track APIs, microservices, and sophisticated AI workloads across distributed infrastructures, especially within Kubernetes and multi-cluster settings. The core capabilities of the platform utilize open-source technologies like Envoy and Istio, featuring Gloo Gateway, which enhances omnidirectional API management by adeptly managing the flow of external, internal, and third-party traffic while maintaining security, authentication, traffic routing, observability, and analytics. Furthermore, Gloo Mesh offers a unified control mechanism for service mesh across multiple clusters, simplifying the connectivity and security of services among various clusters. In addition, the Agentgateway and Gloo AI Gateway provide a secure and regulated traffic pathway for LLM and AI agents, integrating vital guardrails and functionalities to bolster security and performance. This comprehensive strategy empowers enterprises to thrive in a fast-changing technological environment while optimizing their operations efficiently. Ultimately, such robust solutions position businesses to meet the demands of evolving workloads and connectivity needs effectively.

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.

MintMCP acts as a comprehensive Model Context Protocol (MCP) gateway and governance solution tailored for enterprises, presenting a unified strategy for security, observability, authentication, and compliance related to AI tools and agents that interact with internal information, systems, and services. This innovative platform enables organizations to deploy, supervise, and manage their MCP infrastructure on a vast scale, delivering real-time insights into every interaction with MCP tools while incorporating role-based access control and enterprise-level authentication, all while ensuring thorough audit trails that comply with regulatory requirements. Serving as a proxy gateway, MintMCP efficiently consolidates connections from multiple AI assistants, such as ChatGPT, Claude, and Cursor, thereby simplifying monitoring tasks, reducing risky behaviors, securely managing credentials, and enforcing specific policy measures without the need for separate security setups for each individual tool. By centralizing these essential functions, MintMCP not only boosts operational efficiency but also strengthens the security framework of organizations utilizing AI technologies. This integrated approach ultimately allows businesses to focus on their core objectives, knowing their AI interactions are managed securely and effectively.

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.

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.

Klique is a vendor-agnostic enterprise AI control plane that enables organizations to manage AI infrastructure, model access, computing resources, and agentic applications through a centralized platform. The software combines three core capabilities covering intelligent AI request routing, service governance, and GPU workload orchestration. Its smart routing engine directs requests to internally hosted models, open-source models, or external AI providers based on cost, latency, availability, data sensitivity, and organizational policies. Automatic fallback mechanisms allow applications to switch between compatible model providers when preferred services become unavailable or fail to meet defined requirements. The governance engine provides centralized controls for token budgets, spending limits, usage quotas, virtual API keys, single sign-on, and role-based access permissions. Administrators can monitor AI consumption across users, departments, projects, models, and agents while maintaining audit trails and detailed infrastructure cost attribution. GPU orchestration capabilities support resource pooling, fractional GPU sharing, workload prioritization, cloud autoscaling, and allocation of computing resources across multiple clusters. The platform integrates with Kubernetes, Slurm, PBS, AWS, Google Cloud, Azure, and existing GPU infrastructure to support both AI inference and machine learning training workloads. AI development capabilities include experiment tracking, dataset management, model registries, automated pipelines, remote development environments, and deployment of managed inference endpoints. Klique also supports governed agentic development environments for tools such as Claude Code and Codex, alongside Model Context Protocol integrations and self-service application catalogs.

Ensure compliance with corporate guidelines when implementing AI through our intuitive AI governance control plane. By streamlining the experience, you can improve oversight and securely promote the adoption of AI with SurePath AI. This platform integrates effortlessly with your existing security frameworks, proprietary models, and enterprise data sources. It features essential components such as SSO, SCIM, and SIEM. You can monitor AI usage at the network level while controlling access and examining requests to safeguard against potential data breaches. Moreover, it offers the capability to redact sensitive details from requests aimed at public models. The real-time modification of requests enhances operational efficiency while reducing risks. Additionally, you can redirect traffic to your private AI models, leveraging SurePath AI's access controls to craft a custom-branded AI portal for your enterprise. With controls driven by policies, user requests are enhanced with only the data they have permission to access, yielding responses that are particularly relevant to your organizational demands. User prompts are also automatically refined to guarantee that outputs are in line with your strategic goals and ensure adherence to compliance standards. This comprehensive approach not only fortifies security but also fosters a culture of responsible AI use across the organization.

Onyx operates as a comprehensive AI management platform focused on discovering, safeguarding, governing, optimizing, and assessing AI agents and models utilized within a company. It offers vital insights for security, governance, and AI teams regarding both sanctioned and unsanctioned AI operations across diverse environments such as SaaS applications, cloud services, endpoints, and coding practices, covering elements like prompts, responses, and agent conduct. The inclusion of the AI Security feature strengthens the organization’s defense by identifying vulnerabilities and enforcing proactive protections against possible threats and misuse. In parallel, AI Governance guarantees adherence to security protocols and regulatory requirements by providing opt-in coverage and enabling policy regulations to be expressed in natural language. Additionally, AI Orchestration simplifies the deployment of agents and Multi-Cloud Platforms (MCPs), focusing on enhancing cost-effectiveness, precision, and speed. The AI ROI feature aids in quantifying usage, setting targets, and monitoring outcomes across various organizational sectors. Moreover, the Onyx Guardian Agent acts as a supervising AI, consistently detecting risks and addressing challenges throughout the platform, which allows organizations to manage a vast array of agents efficiently. Ultimately, Onyx equips businesses to leverage AI’s full capabilities while ensuring control and diligent oversight, fostering a secure and compliant AI ecosystem. This not only enhances operational efficiency but also encourages innovation within the organization.

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.

WrangleAI stands out as a powerful platform tailored for enterprises, delivering crucial oversight, management, and governance of their AI implementations and associated costs. Acting as a "control plane" for generative AI technologies like GPT-4, Claude, and Gemini, it provides businesses with the ability to monitor usage in real-time, analyze expenses, oversee infrastructure, and set spending thresholds to avoid overspending. Furthermore, WrangleAI improves AI observability, allowing teams to identify which models are being used, by whom, and for what purposes, while facilitating intelligent workload distribution to more cost-effective models without sacrificing quality. The platform also features governance tools, such as role-based access control and compliance support with standards like SOC 2 and ISO 27001, promoting collaboration between finance, engineering, and leadership teams to implement policies and gain actionable insights for refining AI investments. This holistic approach not only enhances the management of AI initiatives but also equips organizations with the knowledge needed to make strategic decisions regarding their AI endeavors, ensuring that they effectively leverage their resources for long-term success. Ultimately, WrangleAI positions itself as an essential ally for enterprises looking to optimize their AI landscapes and drive innovation responsibly.

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.

Maetra acts as a specialized governance control plane designed for teams overseeing AI agents that utilize various tools. It identifies these agents along with their corresponding repositories, evaluates risks through predefined frameworks, and checks possible actions against versioned governance policies before they are carried out. Furthermore, it streamlines the process for human approvals, scrutinizes prompts and tool interactions for vulnerabilities during runtime, guarantees that ongoing tasks stay in line with authorized goals, and preserves immutable records of decisions for auditing. The system consists of multiple modules, including Govern, Secure, Task Guard, Interaction Guard, Discover, Comply, Audit, and Decision Intelligence, which can operate autonomously or collaboratively as a unified control plane, thus improving operational effectiveness and regulatory compliance. This multifaceted approach ultimately fosters a robust framework for managing and overseeing the actions of AI agents within organizations, ensuring that they function within the established guidelines. By promoting accountability and transparency, Maetra strengthens the governance of AI technologies in a rapidly evolving landscape.

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.

Prefect Horizon functions as a comprehensive managed AI infrastructure platform within the broader Prefect product suite, empowering teams to deploy, govern, and oversee Model Context Protocol (MCP) servers and AI agents at an enterprise scale, equipped with crucial production-ready features such as managed hosting, authentication, access control, observability, and governance tools. Utilizing the innovative FastMCP framework, it elevates MCP from a simple protocol to a robust platform composed of four interconnected core components: Deploy, which streamlines the quick hosting and scaling of MCP servers through continuous integration, continuous deployment (CI/CD), and monitoring; Registry, serving as a centralized hub for first-party, third-party, and curated MCP endpoints; Gateway, delivering role-based access control, authentication, and audit trails to ensure secure and regulated access to various tools; and Agents, which provide intuitive interfaces deployable in Horizon, Slack, or accessible via MCP, thereby enabling business users to interact with context-aware AI without needing in-depth technical knowledge of MCP. This comprehensive strategy not only allows organizations to fully leverage AI functionalities but also reinforces their governance and security measures, thus promoting a responsible use of advanced technologies. By integrating these elements, Prefect Horizon presents a solution that meets the intricate demands of modern enterprises in an increasingly data-driven world.

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.

Enkrypt AI is an agentic AI security and compliance platform that helps enterprises identify, mitigate, monitor, and govern risks associated with AI models, applications, agents, and supporting infrastructure. The platform is designed to cover AI security threats and compliance requirements across different models and modalities while allowing organizations to continuously evaluate AI systems as they evolve. Its dynamic red teaming capabilities generate use-case-specific attacks that adapt in real time to uncover security, safety, compliance, and brand risks beyond those identified through static testing. Enkrypt AI can test for threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, drip attacks, unsafe actuation, policy violations, and misuse by end users. It also evaluates AI quality and safety risks such as hallucinations, model drift, bias and discrimination, toxic content, deceptive behavior, misleading outputs, lack of explainability, and brand misalignment. Real-time guardrails detect and stop risky interactions as they occur while adapting to new prompts, behaviors, and emerging threats. Continuous monitoring gives security and compliance teams visibility into AI risks, protection effectiveness, and areas requiring action as models and applications change. Enkrypt AI's compliance functionality converts internal policies and external regulatory requirements into automated guardrails and generates evidence that can support audits and compliance programs. The product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway for protecting AI agents, their data, and their connections to tools and infrastructure. Enkrypt AI supports use cases including customer-facing AI agents, frontier models, AI compliance and auditing, third-party AI risk, secure AI development, data risk assessment, and MCP security.

Unity AI Gateway provides a cohesive platform for managing governance, oversight, and financial management of diverse AI systems within an organization, allowing for the centralized supervision of agents, tools, models, and AI frameworks through a single, regulated interface. This solution promotes uniform governance for AI services, including those hosted on Databricks, external models, coding agents, and agent harnesses, effectively mitigating the risk of vendor lock-in for teams. With policies that consider user identities, it regulates agent access, allowable actions, and tool utilization, while integrated, custom, and third-party protections ensure safety and compliance during prompts, responses, and user interactions. The system meticulously logs prompts, tracks tool interactions, records payloads, maintains audit trails, documents token usage, and captures policy decisions, all of which enhance behavior monitoring, facilitate incident investigations, and support compliance efforts. Additionally, it features centralized financial controls that allow for the tracking of consumption across users, teams, applications, agents, and providers, incorporating budget management, rate limits, and strict spending thresholds to enhance resource allocation efficiency. By simplifying these workflows, Unity AI Gateway not only optimizes the use of AI technologies but also ensures that organizations remain aligned with their governance and financial constraints, making it an essential tool for modern enterprises. Ultimately, this comprehensive approach positions businesses to leverage AI innovations while maintaining accountability and control over their operations.

The ContextForge MCP Gateway is an open-source solution acting as a Model Context Protocol (MCP) gateway, registry, and proxy, providing a unified endpoint for AI clients to access tools, resources, prompts, as well as REST or MCP services within complex AI environments. This system operates in conjunction with various MCP servers and REST APIs, streamlining processes related to discovery, authentication, rate-limiting, observability, and traffic management across numerous backend systems, and supports multiple transport mechanisms such as HTTP, JSON-RPC, WebSocket, SSE, stdio, and streamable HTTP; it also possesses the ability to convert legacy APIs into MCP-compliant tools. Moreover, it includes an optional Admin UI that allows users to configure settings, monitor activities, and access logs in real-time, while being designed to scale from single-instance setups to large multi-cluster Kubernetes environments, utilizing Redis for federation and caching to boost both performance and resilience. This architecture makes the ContextForge MCP Gateway not only a facilitator of seamless interactions within intricate AI architectures but also a highly adaptable platform that can meet the diverse demands of various operational contexts. Ultimately, the platform enhances the overall efficiency and effectiveness of AI integrations, ensuring that users can maximize their technological investments.

Kong AI Gateway acts as an advanced semantic AI gateway that controls and protects traffic originating from Large Language Models (LLMs), allowing for swift integration of Generative AI (GenAI) via innovative semantic AI plugins. This platform enables users to integrate, secure, and monitor popular LLMs seamlessly, while also improving AI interactions with features such as semantic caching and strong security measures. Moreover, it incorporates advanced prompt engineering strategies to uphold compliance and governance standards. Developers find it easy to adapt their existing AI applications using a single line of code, which greatly simplifies the transition process. In addition, Kong AI Gateway offers no-code AI integrations, allowing users to easily modify and enhance API responses through straightforward declarative configurations. By implementing sophisticated prompt security protocols, the platform defines acceptable behaviors and helps craft optimized prompts with AI templates that align with OpenAI's interface. This powerful suite of features firmly establishes Kong AI Gateway as a vital resource for organizations aiming to fully leverage the capabilities of AI technology. With its user-friendly approach and robust functionalities, it stands out as an essential solution in the evolving landscape of artificial intelligence.

FirstHelm acts as a unified control center for overseeing AI agents, functioning as a bridge between your array of agents—such as n8n, OpenAI, Anthropic, CrewAI, LangChain, Microsoft Copilot Studio, or any bespoke agent accessible via REST API—and the larger operational environment. It not only manages the permissions for each agent but also promotes accountability by meticulously logging all actions and validating them against predefined guidelines, including budget constraints, forbidden activities, and transparency regarding costs and tokens allocated per task. Actions considered expensive, risky, or irreversible necessitate human approval prior to execution, with any unattended authorizations designed to expire to prevent delays in decision-making. Furthermore, FirstHelm includes interactive dashboards that enable users to steer agents in real time throughout missions while generating detailed audit trails and compliance records in accordance with regulations such as the EU AI Act, ISO 42001, SOC 2, UK GDPR, NIST AI RMF, and FCA guidelines—covering a total of 38 controls that are assessed continuously based on your individual data. This cutting-edge solution is offered under a freemium pricing structure, is versatile enough to integrate with various frameworks, and hails from the UK, highlighting its focus on adherence to regulations and empowering users. In addition to its intuitive interface and powerful capabilities, FirstHelm is designed to significantly improve the oversight and management of AI-enhanced operations, ultimately streamlining the user experience and enhancing operational efficiency.

Openlayer is an AI governance and observability platform that helps enterprises evaluate, monitor, and control both traditional ML and generative AI systems. The platform is designed for modern AI environments that include LLM applications, RAG pipelines, agentic systems, and complex multi-step workflows. Openlayer provides more than 100 automated tests for evaluating model quality, safety, reliability, data quality, performance, and policy compliance. Teams can use these tests to automate comprehensive model evaluations and identify issues before AI systems affect users, customers, or business operations. The platform’s observability features provide full traceability across prompts, retrieved context, agents, tool usage, intermediate steps, model outputs, and workflow decisions. Real-time guardrails help prevent prompt injections, PII leakage, biased outputs, toxicity, hallucinations, and other AI safety risks. Openlayer supports teams across the full AI lifecycle, from early experimentation and validation to production monitoring and governance reporting. Its governance automation capabilities help organizations align AI development and deployment processes with responsible AI frameworks such as NIST and the EU AI Act. The platform is built for enterprises that need to innovate with AI while maintaining security, compliance, explainability, and operational oversight. Openlayer also helps teams manage risk across both classic machine learning models and newer GenAI systems, giving organizations a unified approach to AI quality and trust. By combining automated testing, observability, real-time protection, traceability, and governance workflows, Openlayer enables safer, more reliable, and more responsible AI operations at scale.

Axway Amplify is an enterprise API management, integration, and AI governance platform built to help organizations connect complex digital ecosystems with more control and flexibility. The platform is federated by design, meaning it can publish, validate, govern, secure, and monitor APIs across multiple clouds, on-premises data centers, vendors, gateways, and repositories. Amplify API Management supports secure API lifecycle management from design through implementation, helping internal and external teams collaborate, reach new markets, and manage APIs across hybrid environments. Amplify Fusion gives IT and business users low-code and no-code tools for building integration flows, automating tasks, designing event-based processes, and reducing the burden on centralized IT teams. Amplify Engage helps enterprises turn APIs and digital assets into discoverable, governed, reusable products through curated marketplaces and developer access controls. Amplify AI Gateway provides a governance layer for production AI usage, including MCP server publishing, prompt guards, prompt templates, LLM orchestration, authentication, authorization, and threat protection. The Amplify Management Plane gives organizations a central place to govern and monitor APIs while allowing development teams to keep using preferred tools and gateways. Amplify Agents help capture API value by making APIs easier to discover, reuse, and govern across environments such as AWS, Azure, Istio, and other gateway systems. The platform supports a broader range of API patterns beyond SOAP and REST, including GraphQL, events, service mesh, gRPC, and AsyncAPI. Because Amplify is modular, organizations can start with federated API management, low-code integration, API adoption, or AI governance and scale the platform as their architecture matures.

Earthly Lunar helps platform and engineering leaders keep software delivery consistent as teams, repositories, and AI-assisted code volume grow. Instead of asking each team to maintain its own checklist or CI template, Lunar collects development lifecycle signals centrally from repositories and CI/CD systems. It creates a structured picture of each service's tests, dependencies, build and deployment practices, then evaluates organization-wide engineering guardrails against that picture. Leaders can see which standards are being followed, where exceptions appear, and how adoption changes across teams. Platform teams can start with monitoring, add pull request feedback, and graduate selected rules to blocking enforcement. Prebuilt and custom guardrails cover testing, quality, operational readiness, infrastructure, and compliance requirements. This approach gives teams flexibility in their tools while applying the same expectations to human-written and AI-generated code. The resulting enforcement history also supports audit preparation and post-incident follow-through.

Kosmoy brings AI inventory, monitoring, gateway policies and agent runtime controls into one enterprise platform. Teams register models, applications, agents and MCP servers, assign owners and assess risks. They can monitor usage, costs and behaviour, then apply access controls, guardrails, routing and logging through the AI Gateway. Action Capsule adds runtime isolation and a kill switch for autonomous agents. The platform is deployed in the customer Kubernetes environment, on premises or in the cloud. It is designed for AI platform, security, risk and compliance teams that need to connect governance decisions to the AI systems they operate. Enterprise licensing is quoted for the deployment scope and capabilities required.

Gate22 functions as a comprehensive platform for AI governance and Model Context Protocol (MCP) control that is tailored for enterprises, providing centralized management of the security and oversight of AI tools and agents interacting with MCP servers. It enables administrators to onboard, configure, and manage both internal and external MCP servers, offering granular permissions at the functional level, team-oriented access controls, and role-specific policies to guarantee that only approved tools and capabilities are accessible to the appropriate teams or individuals. By delivering a unified MCP endpoint, Gate22 consolidates multiple MCP servers into an easily navigable interface with just two main functions, which helps to lessen token consumption for developers and AI clients while effectively reducing context overload and maintaining both accuracy and security. The platform features an administrative interface with a governance dashboard that tracks usage patterns, ensures compliance, and applies least-privilege access, while the member interface streamlines and secures access to authorized MCP bundles. This dual perspective not only enhances operational productivity but also fortifies the overall security infrastructure within the organization. Additionally, the integration of these functionalities fosters a collaborative environment where teams can work more effectively while adhering to compliance standards.