# portkey-ai/gateway

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12,091 stars · 1,132 forks · TypeScript · MIT

## Links

- GitHub: https://github.com/Portkey-AI/gateway
- Homepage: https://portkey.ai/features/ai-gateway
- awesome-repositories: https://awesome-repositories.com/repository/portkey-ai-gateway.md

## Topics

`ai-gateway` `gateway` `generative-ai` `hacktoberfest` `langchain` `llm` `llm-gateway` `llmops` `llms` `mcp` `mcp-client` `mcp-gateway` `mcp-servers` `model-router` `openai`

## Description

This project is an artificial intelligence gateway that functions as a centralized middleware layer for managing, securing, and observing interactions with language, vision, and audio models. It provides a unified interface that standardizes requests across multiple providers, enabling teams to integrate AI capabilities into their applications through a consistent set of tools and protocols.

The gateway distinguishes itself through its comprehensive infrastructure governance and traffic management capabilities. It allows for policy-driven routing, automated failover, and load balancing across different model providers to ensure high availability. Furthermore, it incorporates real-time security guardrails, sensitive data redaction, and virtual credential management, which abstracts provider-specific keys to facilitate secure access control and usage attribution across organizational units.

Beyond its core proxying functions, the platform offers extensive observability and operational tools. It captures detailed telemetry, including performance metrics, request tracing, and cost analytics, while providing a centralized repository for prompt versioning and template management. The system also supports semantic response caching to reduce latency and operational costs, alongside features for auditing, feedback collection, and fine-tuning model outputs.

The software is designed for deployment within private networks or cloud environments, ensuring full data ownership and compliance with internal security requirements.

## Tags

### Artificial Intelligence & ML

- [AI Request Routing](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-request-routing.md) — Distributes requests across multiple AI models using load balancing, fallbacks, and retries to ensure high availability. ([source](https://cdn.jsdelivr.net/gh/Portkey-AI/gateway@main/README.md))
- [LLM Middleware](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-middleware.md) — Functions as a middleware layer that standardizes requests, manages provider credentials, and enforces security guardrails for AI applications.
- [AI Governance Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-governance-tools.md) — Manages organizational access, security policies, and data privacy requirements for large-scale AI deployments.
- [AI Guardrails](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-guardrails.md) — Enforces real-time safety checks and sensitive data redaction to protect AI applications from malicious or non-compliant interactions.
- [AI Observability Tracing](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-observability-tracing.md) — Provides a centralized system for tracing request lifecycles, logging model interactions, and analyzing usage costs across teams.
- [Prompt Management Systems](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-management-systems.md) — Offers a centralized repository for versioning, testing, and organizing prompt templates to ensure consistent engineering workflows.
- [Agent Prompt Templates](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/integration-deployment/agent-frameworks/configuration-and-specifications/agent-prompt-templates.md) — Provides centralized management for prompt versioning and template libraries to streamline agent development workflows.
- [AI Application Monitoring](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-application-monitoring.md) — Tracks request-level cost, latency, and error rates to provide visibility into how AI applications behave in production. ([source](https://portkey.ai/features/agents))
- [Semantic Caching Systems](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-inference-serving/request-routing-gateways/semantic-caching-systems.md) — Stores and retrieves model outputs based on semantic request content to reduce latency and operational costs.
- [Model Context Protocol](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/model-integration-serving/model-integration-interfaces/model-context-protocol.md) — Provides a standardized protocol interface for connecting AI models to local data sources and external tools. ([source](https://portkey.ai/docs/product/mcp-gateway/quickstart))
- [MCP Server Management](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/model-integration-serving/model-integration-interfaces/model-context-protocol/mcp-server-management.md) — Provides a centralized control plane for authenticating and monitoring access to protocol servers. ([source](https://cdn.jsdelivr.net/gh/Portkey-AI/gateway@main/README.md))
- [Agent Framework Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-framework-integrations.md) — Connects prompt management workflows with external agent orchestration tools to streamline complex AI application development. ([source](https://portkey.ai/features/prompt-management))
- [Human Feedback Collection](https://awesome-repositories.com/f/artificial-intelligence-ml/human-feedback-collection.md) — Gathers structured qualitative and quantitative user feedback at the request level to evaluate response quality. ([source](https://portkey.ai/docs/integrations/agents))
- [Prompt Registries](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-registries.md) — Centralizes prompt storage to facilitate versioning, A/B testing, and rapid iteration across multiple models. ([source](https://portkey.ai/features/prompt-management))
- [Prompt Templates](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-templates.md) — Groups prompts into shared templates to enable team-wide access and consistent prompt engineering workflows. ([source](https://portkey.ai/features/prompt-management))
- [Model Fine-Tuning](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-training-and-tuning/fine-tuning-and-customization/model-fine-tuning.md) — Improves response quality by applying provider-specific fine-tuning configurations through a consistent interface. ([source](https://portkey.ai/features/ai-gateway))
- [Model Comparison Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/model-comparison-tools.md) — Runs prompts across multiple language models simultaneously to analyze output quality and performance in a unified environment. ([source](https://portkey.ai/features/prompt-management))

### DevOps & Infrastructure

- [AI Model Load Balancers](https://awesome-repositories.com/f/devops-infrastructure/traffic-load-balancers/ai-model-load-balancers.md) — Distributes requests across multiple AI model providers using load balancing and automated failover to ensure high availability.
- [Safety-based Routing](https://awesome-repositories.com/f/devops-infrastructure/api-service-management/api-management/ai-traffic-routing/safety-based-routing.md) — Directs traffic based on guardrail results by denying risky requests or switching to alternative models. ([source](https://portkey.ai/features/guardrails))
- [Private Infrastructure Management](https://awesome-repositories.com/f/devops-infrastructure/infrastructure/private-enterprise-management/self-hosted-services/private-infrastructure-management.md) — Supports deployment within private networks or cloud environments to ensure full data ownership and operational control. ([source](https://portkey.ai/docs/self-hosting/hybrid-deployments/architecture))

### Networking & Communication

- [Model Request Proxies](https://awesome-repositories.com/f/networking-communication/model-request-proxies.md) — Intercepts and routes API requests to interchangeable language model providers with centralized authentication and logging. ([source](https://portkey.ai/docs/product/mcp-gateway))
- [Traffic Routing Policies](https://awesome-repositories.com/f/networking-communication/traffic-routing-policies.md) — Distributes requests across multiple model endpoints using conditional logic and load balancing to ensure high availability.
- [Integration Layers](https://awesome-repositories.com/f/networking-communication/integration-layers.md) — Connects disparate agent frameworks and tools through a standardized interface for consistent interaction across environments.

### Security & Cryptography

- [Model Safety Filters](https://awesome-repositories.com/f/security-cryptography/model-safety-filters.md) — Validates model inputs and outputs against security checks and prompt filters to prevent harmful content. ([source](https://cdn.jsdelivr.net/gh/Portkey-AI/gateway@main/README.md))
- [Virtual Key Managers](https://awesome-repositories.com/f/security-cryptography/virtual-key-managers.md) — Manages virtualized API credentials with usage tracking and rotation for multi-tenant AI environments. ([source](https://portkey.ai/features/security-compliance))
- [API Gateway Security](https://awesome-repositories.com/f/security-cryptography/api-gateway-security.md) — Provides centralized proxy-based security and authentication management for AI model interactions. ([source](https://portkey.ai/docs/product/mcp-gateway))
- [Data Redaction Tools](https://awesome-repositories.com/f/security-cryptography/data-redaction-tools.md) — Automatically strips sensitive information from outgoing AI model requests to ensure data privacy. ([source](https://portkey.ai/features/security-compliance))
- [Model Access Controls](https://awesome-repositories.com/f/security-cryptography/identity-access-management/access-control/access-control-models/model-access-controls.md) — Controls access to specific AI models and providers to manage costs and compliance across teams. ([source](https://portkey.ai/features/model-catalog))
- [Model Access Governance](https://awesome-repositories.com/f/security-cryptography/model-access-governance.md) — Manages user permissions, team budgets, and role-based access across organizational levels to ensure secure and governed model usage. ([source](https://portkey.ai/for/azure))
- [Security Guardrails](https://awesome-repositories.com/f/security-cryptography/security-guardrails.md) — Applies real-time security filters and validation logic to request and response payloads to ensure compliance.
- [Data Encryption](https://awesome-repositories.com/f/security-cryptography/data-encryption.md) — Secures data at rest and in transit using cryptographic standards and customer-managed keys. ([source](https://portkey.ai/docs/self-hosting/hybrid-deployments/architecture))
- [Network Access Control](https://awesome-repositories.com/f/security-cryptography/network-access-control.md) — Filters incoming requests based on IP addresses to enforce infrastructure access security. ([source](https://portkey.ai/features/security-compliance))
- [Traffic Isolation](https://awesome-repositories.com/f/security-cryptography/account-management/traffic-isolation.md) — Segregates operational metrics from sensitive request content to ensure anonymized data handling. ([source](https://portkey.ai/docs/self-hosting/hybrid-deployments/architecture))

### Business & Productivity Software

- [AI Usage Analytics](https://awesome-repositories.com/f/business-productivity-software/spend-tracking-tools/ai-usage-analytics.md) — Tracks, attributes, and optimizes financial expenditure and performance metrics across various language models.

### Data & Databases

- [Response Caching](https://awesome-repositories.com/f/data-databases/response-caching.md) — Stores and retrieves previous model outputs for identical or semantically similar queries to reduce latency and operational costs. ([source](https://portkey.ai/docs/integrations/agents))
- [Data Governance](https://awesome-repositories.com/f/data-databases/data-governance-modeling/data-management-governance/data-governance.md) — Enforces data privacy and compliance through isolated storage and custom retention policies. ([source](https://portkey.ai/for/enterprise))

### Software Engineering & Architecture

- [Resilient Deliberation Strategies](https://awesome-repositories.com/f/software-engineering-architecture/failure-handling-policies/resilient-deliberation-strategies.md) — Maintains service continuity through automated retries and fallback mechanisms between different AI models. ([source](https://portkey.ai/features/ai-gateway))
- [Request Interception Middleware](https://awesome-repositories.com/f/software-engineering-architecture/request-interception-middleware.md) — Intercepts incoming API traffic to perform authentication, logging, and policy enforcement before forwarding to model providers.

### System Administration & Monitoring

- [AI Cost Monitoring](https://awesome-repositories.com/f/system-administration-monitoring/ai-cost-monitoring.md) — Tracks and categorizes standardized cost metrics across AI models by application or team to assist with budget planning. ([source](https://portkey.ai/models))
- [Usage Limiters](https://awesome-repositories.com/f/system-administration-monitoring/usage-limiters/usage-limiters.md) — Caps financial expenditure and request frequency per API key to prevent resource exhaustion. ([source](https://portkey.ai/for/enterprise))
- [Agent Execution Tracing](https://awesome-repositories.com/f/system-administration-monitoring/agent-execution-tracing.md) — Records the full lifecycle of agent interactions and request journeys to simplify debugging and identify bottlenecks. ([source](https://portkey.ai/features/agents))
- [Observability Pipelines](https://awesome-repositories.com/f/system-administration-monitoring/observability-pipelines.md) — Aggregates logs, traces, and performance metrics from diverse AI workflows into a standardized format for auditing.
- [System Audit Trails](https://awesome-repositories.com/f/system-administration-monitoring/system-audit-trails.md) — Maintains comprehensive logs of all model interactions and feedback data to ensure compliance and operational transparency. ([source](https://portkey.ai/for/azure))
- [Activity Monitors](https://awesome-repositories.com/f/system-administration-monitoring/activity-monitors.md) — Records logs of configuration changes and user actions across workspaces to ensure accountability and compliance. ([source](https://portkey.ai/for/org-wide-audit-logs))
- [Logging and Telemetry](https://awesome-repositories.com/f/system-administration-monitoring/logging-and-telemetry.md) — Records interactions with language models and tools, including parameters and responses, to provide visibility into usage patterns. ([source](https://portkey.ai/features/observability))
- [Audit Log Filters](https://awesome-repositories.com/f/system-administration-monitoring/audit-log-filters.md) — Isolates specific events by resource, user, or network origin to enable rapid incident investigation and security auditing. ([source](https://portkey.ai/for/org-wide-audit-logs))
- [Automatic Tracing Instrumentation](https://awesome-repositories.com/f/system-administration-monitoring/automatic-tracing-instrumentation.md) — Captures logs, traces, and metrics from language model frameworks automatically without requiring manual integration code. ([source](https://portkey.ai/features/observability))

### Part of an Awesome List

- [Application Development](https://awesome-repositories.com/f/awesome-lists/ai/application-development.md) — Unified API gateway for managing requests to multiple models.
- [Infrastructure and Gateways](https://awesome-repositories.com/f/awesome-lists/ai/infrastructure-and-gateways.md) — Fast AI gateway for routing to multiple LLMs.
- [Privacy and Safety](https://awesome-repositories.com/f/awesome-lists/security/privacy-and-safety.md) — AI gateway with integrated guardrails for model safety.

### Testing & Quality Assurance

- [Agent Input and Output Validators](https://awesome-repositories.com/f/testing-quality-assurance/validation-verification/input-validation/agent-input-and-output-validators.md) — Inspects and validates agent responses in real time to ensure content standards and prevent data leaks. ([source](https://portkey.ai/features/agents))
- [Standardized Interfaces](https://awesome-repositories.com/f/testing-quality-assurance/api-network-testing/api-testing/api-and-ui-integration-tools/standardized-interfaces.md) — Exposes a standardized interface mirroring industry SDKs to facilitate integration with existing development tools. ([source](https://portkey.ai/for/sme))