What is an MCP Gateway?

An MCP Gateway is a centralized control plane that securely manages access, discovery, and orchestration of MCP Servers across an enterprise. It acts as the operational backbone for agentic AI systems by enabling AI agents and applications to interface with enterprise tools via a standardized protocol. With support for authentication, RBAC, observability, and workflow execution, the MCP Gateway makes connecting and scaling intelligent systems seamless and secure.

What is an MCP Server and how does it work with the MCP Gateway?

An MCP Server (Model Context Protocol Server) is a standardized interface layer that wraps around enterprise APIs or tools, making them easily discoverable and callable by AI agents. When integrated with an MCP Gateway, each MCP Server registers itself, becomes accessible through a unified endpoint, and inherits enterprise-grade features like RBAC, federated authentication (via Okta, Azure AD), and observability—making orchestration across tools like Slack, Jira, or internal APIs effortless.

How do I build and deploy an MCP Server?

You can build an MCP Server using TrueFoundry’s SDK or your preferred backend stack. MCP Servers are containerized and typically deployed on Kubernetes or cloud-native infrastructure. Once live, they register with the MCP Gateway and are made available for secure discovery and task execution via agents or users—streamlining the AI integration pipeline.

What are the key features of an MCP Gateway?

The MCP Gateway provides unified access to all registered MCP Servers, instant discovery via a central registry, and secure access control with OAuth 2.0 and federated identity providers. It enables agentic task execution across tools, offers enterprise-grade observability with request-level tracing and audit logs, supports out-of-the-box and custom integrations (e.g., Slack, Datadog, internal APIs), and ensures high-performance operation across cloud, on-prem, and hybrid environments.

What are the benefits of using an MCP Gateway in enterprise environments?

There are various benefits of using an MCP Gateway in enterprise environments. It dramatically simplifies tool integrations, accelerates onboarding via prebuilt MCP Servers, and unifies security and compliance controls. It enables plug-and-play agentic workflows, supports distributed environments, and provides deep observability for cost and performance. The result is a scalable, secure, and maintainable AI system capable of handling real-time enterprise workloads with minimal engineering effort.

How does the MCP Gateway handle authorization and access control?

Authorization is enforced through Role-Based Access Control (RBAC) policies integrated with enterprise Identity Providers such as Okta or Azure AD. Each MCP Server, endpoint, or tool function can be governed by specific access rules, ensuring only authorized users or agents can trigger actions or retrieve sensitive data.

Can I use my existing SSO or IdP with the MCP Gateway?

Yes, the MCP Gateway and all MCP Servers fully support existing enterprise identity providers. Federated login via Okta, Azure AD, or custom SSO setups is supported out-of-the-box, enabling seamless integration into your organization's existing authentication and compliance stack.

What enterprise tools can I connect using MCP Servers?

You can integrate both standard and proprietary tools. MCP Gateway offers prebuilt MCP Servers for platforms like Slack, Confluence, Datadog, and Sentry. Additionally, you can create custom MCP Servers to connect any internal service, REST API, or data platform—extending orchestration across your unique tech stack.

How does MCP Gateway enable agentic task execution?

Through the MCP Gateway, AI agents can autonomously discover, authenticate, and call MCP Servers. This enables them to execute multi-step workflows (e.g., “create a Jira ticket from Slack messages”), generate and run code, or orchestrate tools—all governed by standardized interactions and enterprise policies.

What kind of observability does the MCP Gateway offer?

The MCP Gateway provides full visibility into every interaction with MCP Servers. It supports end-to-end tracing, metadata tagging (e.g., team, user, tool), and audit logging for compliance. Enterprises can monitor latency, usage, errors, and cost attribution in real-time—ensuring traceability and control across AI workloads.

Is the MCP Gateway secure and scalable for enterprise deployment?

Absolutely. The MCP Gateway is designed for production-grade deployments. It supports federated SSO, OAuth 2.0, dynamic discovery, multi-region failover, and role-based security—all while operating at high throughput under real-time enterprise load. It’s built to power large-scale, AI-first systems with confidence.

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سجل المطالبات المركزي

أدر جميع المطالبات من سجل واحد مشترك بدلاً من ترميزها الثابت عبر التطبيقات.

إدارة إصدارات المطالبات

تتبع كل تغيير في المطالبات بسجل إصدارات كامل، وارجع فورًا إلى إصدار سابق عند الحاجة.

الترقية المستندة إلى البيئة

انقل المطالبات بأمان عبر بيئات التطوير والتدريج والإنتاج باستخدام مسارات عمل محكمة.

اختبار المطالبات والتحقق منها

اختبر سلوك المطالبات مقابل المدخلات والنماذج التجريبية قبل نشرها في بيئة الإنتاج.

التحكم في الوصول والحوكمة

تحكم في من يمكنه تحرير المطالبات ومراجعتها ونشرها باستخدام التحكم في الوصول المستند إلى الأدوار.

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استخدم المطالبات المدارة عبر الوكلاء وطلبات بوابة الذكاء الاصطناعي دون الحاجة لإعادة نشر التطبيقات.

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مستودع المطالبات المركزي

إدارة جميع المطالبات في مكان واحد بدلاً من تشتيتها عبر قواعد الأكواد.

تخزين وإدارة المطالبات مركزيًا بدلاً من ترميزها الثابت في التطبيقات
تنظيم المطالبات حسب المشروع أو البيئة أو حالة الاستخدام
مشاركة المطالبات عبر الفرق مع ملكية واضحة وضوابط وصول
إعادة استخدام المطالبات بشكل متسق عبر النماذج والوكلاء والخدمات

اقرأ المزيد

تحديد إصدار المطالبات وسجلها

تتبع كل تغيير يتم إجراؤه على مطالبة مع سجل إصدارات كامل.

تحديد إصدار المطالبات تلقائيًا مع كل تحديث
عرض الإصدارات السابقة ومقارنة التغييرات
العودة إلى الإصدارات السابقة فورًا في حال ظهور مشكلات
الاحتفاظ بسجل تدقيق يوضح من قام بالتغيير وماذا ومتى

اقرأ المزيد

ترحيل المطالبات حسب البيئة

ترحيل المطالبات بأمان من بيئة التطوير إلى بيئة الإنتاج.

الاحتفاظ بمطالبات منفصلة لبيئات التطوير والتدريج والإنتاج
ترحيل إصدارات المطالبات المعتمدة عبر البيئات
Prevent untested prompt changes from impacting production traffic
Align prompt changes with deployment and release workflows

MCP Gateway Tool Discovery for MCP servers

Access Control & Governance for Prompts

Control who can create, modify, and deploy prompts.

Apply role-based access control (RBAC) to prompts
Restrict who can edit or promote prompts
Enforce review and approval workflows
Maintain compliance and auditability

Works Seamlessly with Agents and AI Gateway

Design, test, and ship prompts directly into production AI workflows.

Select and test prompt versions in the Playground before serving them via the AI Gateway
Generate ready-to-use code snippets with prompt version identifiers for agents and applications
Update prompts centrally without redeploying services or agents
Ensure consistent prompt behavior across models, environments, and AI workloads

Made for Real-World AI at Scale

99.99%

uptime

Centralized failovers, routing, and guardrails ensure your AI apps stay online, even when model providers don’t.

10B+

Requests processed/month

Scalable, high-throughput inference for production AI.

30%

Average cost optimization

Smart routing, batching, and budget controls reduce token waste.

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انشر بوابة ذكاء اصطناعي آمنة تحافظ على بياناتك ونماذجك ضمن بنيتك التحتية السحابية / المحلية.

HIPAA, GDPR, and AICPA SOC compliance badges for data security and privacy regulations standards.

الامتثال والأمان
معايير SOC 2 و HIPAA و GDPR لضمان حماية قوية للبيانات
الحوكمة والتحكم في الوصول
تسجيل الدخول الموحد (SSO) + التحكم في الوصول المستند إلى الأدوار (RBAC) وتسجيل التدقيق
دعم وموثوقية للمؤسسات
دعم على مدار الساعة طوال أيام الأسبوع مع اتفاقيات مستوى خدمة للاستجابة مدعومة بضمانات

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Real Outcomes at TrueFoundry

Why Enterprises Choose TrueFoundry

3x

faster time to value with autonomous LLM agents

80%

higher GPU‑cluster utilization after automated agent optimization

Aaron Erickson

Founder, Applied AI Lab

TrueFoundry turned our GPU fleet into an autonomous, self‑optimizing engine - driving 80 % more utilization and saving us millions in idle compute.

5x

faster time to productionize internal AI/ML platform

50%

lower cloud spend after migrating workloads to TrueFoundry

Pratik Agrawal

Sr. Director, Data Science & AI Innovation

TrueFoundry helped us move from experimentation to production in record time. What would've taken over a year was done in months - with better dev adoption.

80%

reduction in time-to-production for models

35%

cloud cost savings compared to the previous SageMaker setup

Vibhas Gejji

Staff ML Engineer

We cut DevOps burden and simplified production rollouts across teams. TrueFoundry accelerated ML delivery with infra that scales from experiments to robust services.

50%

faster RAG/Agent stack deployment

60%

reduction in maintenance overhead for RAG/agent pipelines

Indroneel G.

Intelligent Process Leader

TrueFoundry helped us deploy a full RAG stack - including pipelines, vector DBs, APIs, and UI—twice as fast with full control over self-hosted infrastructure.

60%

faster AI deployments

~40-50%

Effective Cost reduction of across dev environments

Nilav Ghosh

Senior Director, AI

With TrueFoundry, we reduced deployment timelines by over half and lowered infrastructure overhead through a unified MLOps interface—accelerating value delivery.

<2

weeks to migrate all production models

75%

reduction in data‑science coordination time, accelerating model updates and feature rollouts

Rajat Bansal

CTO

We saved big on infra costs and cut DS coordination time by 75%. TrueFoundry boosted our model deployment velocity across teams.

Frequently asked questions

What is Prompt Management in TrueFoundry?

Prompt Management in TrueFoundry provides a centralized system to create, version, test, and govern prompts used across LLM-powered applications, agents, and workflows. It allows teams to treat prompts as first-class assets just like code or models ensuring consistency, traceability, and controlled evolution of prompts in production AI systems.

How does Prompt Management integrate with the AI Gateway and agents?

Prompt Management is deeply integrated with the AI Gateway and agent execution layer. Prompts defined in the Prompt Registry can be directly selected and executed from the Playground, referenced by agents at runtime, and invoked through the AI Gateway using stable prompt identifiers. This ensures that changes to prompts are versioned, auditable, and safely propagated across applications without breaking production behavior.

Can I test and iterate on prompts before deploying them to production?

Yes. The Prompt Playground allows you to experiment with prompts interactively using real models, configurations, and tools. You can test different prompt variants, model parameters, and inputs, observe outputs in real time, and compare results before promoting a prompt version to production. This enables rapid iteration while maintaining confidence in prompt quality and behavior.

How does prompt versioning work in TrueFoundry?

Every prompt is automatically versioned when updated, allowing teams to track changes over time and maintain a full history of prompt evolution. Each version can be referenced independently, rolled back if needed, and compared against other versions. This makes it easy to safely update prompts without introducing regressions in downstream applications or agents.

How do I use prompts programmatically in my applications?

TrueFoundry generates production-ready code snippets for each prompt version, allowing you to invoke prompts directly via the AI Gateway using APIs or SDKs. These snippets include prompt identifiers, version references, and model configuration details, making it easy to integrate prompts into applications, agents, or workflows without hardcoding prompt text.

Does Prompt Management support collaboration and access control?

Yes. Prompt Management supports role-based access control (RBAC), enabling teams to define who can create, edit, approve, or deploy prompts. This is especially useful in enterprise settings where prompt changes must go through review processes or be restricted to specific teams. All changes are logged for auditability and governance.

Can Prompt Management be used across multiple environments?

Prompt Management works seamlessly across development, staging, and production environments. Teams can test prompts in isolated environments and promote approved versions to production while maintaining consistent behavior and governance across the AI stack.

How is Prompt Management different from storing prompts in code?

Unlike prompts stored directly in application code, TrueFoundry’s Prompt Management provides versioning, observability, access control, and runtime flexibility. Prompts can be updated, tested, and rolled back independently of application deployments, reducing operational risk and speeding up iteration for AI teams.