Exploring MCP Gateways (2025): Find the best MCP for you

Exploring MCP Gateways (2025): How Requesty and Others Simplify AI Tool Access

Introduction

Large language models (LLMs) and autonomous agents often need to execute actions like querying a database, updating a CRM or invoking a Python script. Model Context Protocol (MCP), introduced by Anthropic in late 2024, standardizes how AI assistants discover and use external tools. Instead of manually coding one‑off integrations, MCP lets AI clients call tools and resources through a consistent JSON‑RPC interface. However, connecting to dozens of individual MCP servers creates complexity: each server has its own authentication, context format, rate limits and logging. A March 2025 article on Hookdeck explained that managing multiple servers increases complexity, security risks, context drift and operational overhead[1]. A September 2025 guide on Skywork.ai described the alternative: an MCP gateway is a session‑aware reverse proxy and lightweight control plane that fronts many servers behind one endpoint, adding routing, centralized authentication, policy enforcement and observability[2]. This blog surveys the major MCP gateway options and highlights why Requesty’s MCP Gateway stands out.

Why Choose a Gateway Instead of Individual Servers?

An MCP gateway sits between AI agents and multiple MCP servers. Skywork.ai notes that a gateway aggregates a fleet of servers so multi‑step workflows consistently hit the right backend, unifies authentication and rate limiting, and provides standardized discovery and lifecycle APIs[3]. The same source points out that gateways are ideal for multi‑agent platforms, regulated environments or enterprises consolidating secrets and audit trails[4]. In contrast, direct connections to each server are easier for quick prototypes but lead to sprawl, fragmented observability and independent scaling[5].

Requesty MCP Gateway: Universal Compatibility and Enterprise Control

Requesty’s MCP Gateway (docs.requesty.ai) is designed for teams who want to tap into MCP tooling quickly while maintaining security and observability. Universal compatibility is a key benefit—the service supports tools built with Claude Code, Cursor IDE, Roo Code, VS Code extensions and HTTP/CLI‑based servers[6]. With a single dashboard, teams can register multiple MCP servers, whitelist only the tools they trust, manage API keys and monitor usage. Key features include:

• Centralized server management: administrators can register MCP servers via pre‑built templates (GitHub, Notion, Linear, Context7) or provide a custom URL and authentication headers[7]. The dashboard displays server health status, throughput and error rates[8].

• Flexible authentication models: the Standard Plan uses organization‑wide keys for quick start‑up, while the Enterprise Plan gives each user a unique key, supporting granular permissions and user‑level audit trails[9].

• Per‑user key management: Requesty stores user keys with AES‑256 encryption[10] and enforces isolation, ensuring users cannot access each other’s tools[11]. Audit logs capture key creation, tool usage and security events for compliance[12].

• Real‑time analytics: the analytics dashboard tracks request volume, latency, success rates, unique users and cost metrics across configurable time periods[13][14]. Teams can drill into server performance, tool usage patterns, user activity and historical trends[15][16].

• AI tool integration: Requesty integrates with coding assistants such as Claude Code and Cursor. Tools are automatically discovered, and AI agents can call them using natural language; advanced features include tool chaining, context awareness and performance optimization[17][18]【760588038513272†screenshot】. A centralized gateway also prevents AI assistants from connecting to unauthorized servers[19].

Requesty effectively combines tool discovery, granular access control, enterprise‑grade security and rich analytics—making it our favored solution for production environments.

TrueFoundry MCP Gateway (2025): Unified AI Infrastructure

TrueFoundry, an AI‑infrastructure company, released its own MCP Gateway in July 2025. Its core philosophy is to avoid fragmenting AI workloads across multiple systems. Key points from TrueFoundry’s blog include:

• Ultra‑low latency: authentication and rate‑limiting occur in memory, enabling sub‑3 ms latency under load. This matters when agents make hundreds of tool calls per conversation.

• Centralised & integrated infrastructure: MCP Server Groups provide logical isolation so different teams can experiment without creating security holes. The gateway shares security, observability and performance characteristics with TrueFoundry’s AI Gateway (LLM serving), giving organizations a single control panel for models and tools.

• Unified billing and observability: metrics and costs for LLMs and tools appear in one dashboard.

TrueFoundry targets organizations already managing significant AI workloads who want to extend existing infrastructure rather than adopt a standalone MCP solution. It is best for enterprises comfortable with TrueFoundry’s AI platform.

Docker MCP Gateway: Secure Containers for Tools

Docker’s open‑source MCP Gateway treats MCP servers as container workloads. Its documentation describes it as an orchestrator that unifies multiple servers into a single endpoint and provides enterprise‑ready observability and secrets management[20]. Features include:

• Container isolation: each server runs in its own container with limited CPU and memory; cryptographically signed images offer supply‑chain security.

• Secrets management and dynamic discovery: servers can be registered dynamically, and policies enforce secure communication and environment isolation[20].

• Developer convenience: Docker Desktop integration simplifies setup, making it ideal for teams already using containerized infrastructures.

Docker’s gateway is well suited to organizations that prioritize container security and developer experience.

IBM Context Forge (MCP Gateway): Federation and Flexibility

IBM’s Context Forge (hosted on GitHub) is an open‑source gateway, proxy and registry that federates both MCP and REST services. The project can unify discovery, authentication, rate‑limiting and observability while composing multiple MCP servers into a single endpoint[21]. TrueFoundry’s review highlights additional capabilities:

• Federation features: auto‑discovery via mDNS, health monitoring and capability merging allow multiple gateways to work together.

• Flexible authentication: supports JWT bearer tokens, basic auth and custom headers; credentials are AES‑encrypted.

• Multi‑database support: connectors for PostgreSQL, MySQL and SQLite facilitate integration with existing enterprise systems.

Context Forge appeals to organizations with sophisticated DevOps teams who need multi‑cluster deployments and are comfortable operating an open‑source project with limited commercial support.

Microsoft MCP Gateway (Azure Integration)

Microsoft’s open‑source gateway is tightly integrated into the Azure ecosystem. The Skywork.ai guide notes that Microsoft provides multiple MCP integration points across Azure services—Azure AD for authentication, API Management for policy enforcement, Container Apps for scalable deployment and Azure Monitor for observability. This approach eliminates separate authentication complexity for Azure customers and leverages existing cloud investments. The downside is potential vendor lock‑in and a more complex setup compared with purpose‑built solutions. Microsoft’s gateway is ideal for teams already invested in Azure and comfortable with its governance models.

Lasso Security Gateway: Guardrails for AI Safety

Lasso Security, recognized by Gartner for AI security, offers a security‑centric MCP gateway. According to the company’s press release, the gateway acts as a proxy/orchestrator for MCP interactions, embedding security, governance and monitoring capabilities[22]. Key capabilities include:

• Agnostic guardrails: configurable security filters prevent sensitive data exposure, prompt injection and command injection[23][24].

• Advanced tracking & unified visibility: comprehensive usage analytics and dashboards show which tools are being accessed and by whom[23].

• Plugin‑based security: TrueFoundry’s analysis notes that Lasso offers a plugin architecture for real‑time threat detection, token masking and AI safety guardrails; tool reputation analysis scores servers based on behavior patterns.

Lasso is suited for organizations in regulated industries or handling sensitive data where comprehensive security monitoring is paramount.

Other Notable MCP Gateway Solutions

The MCP ecosystem is evolving quickly. Below is a summary of other gateways and their differentiators. (These are described briefly because full coverage would require a separate deep dive.)

Choosing the Right MCP Gateway

Selecting an MCP gateway depends on your organization’s infrastructure, security posture and development goals. Skywork.ai’s decision matrix suggests choosing direct MCP servers for proof‑of‑concepts, gateways for multi‑agent and regulated environments, and hybrid approaches for gradual migration[47]. TrueFoundry’s evaluation matrix compares latencies, concurrency and management complexity across vendors: TrueFoundry’s sub‑3 ms latency and extensive observability suit large AI workloads, Docker offers container isolation with moderate latency, IBM delivers flexibility at the cost of support, Microsoft integrates deeply with Azure, and Lasso prioritizes security.

Conclusion

The MCP gateway landscape has evolved rapidly since 2024. Many vendors offer specialized solutions: TrueFoundry emphasizes unified AI infrastructure and performance, Docker focuses on container isolation, IBM provides federation and flexibility, Microsoft integrates into Azure, Lasso prioritizes security, and a host of other providers build gateways around specific ecosystems. Among these, Requesty distinguishes itself through its universal compatibility, enterprise‑grade security, per‑user key management, real‑time analytics and developer‑friendly integrations. Whether you are just starting with AI tools or running enterprise‑scale agents, a thoughtfully chosen MCP gateway—particularly one like Requesty—can centralize tool access, reduce security risks and give your team the observability needed to build trustworthy, scalable AI applications.