AI agents are ungoverned
Your teams are deploying AI agents that can create GitHub issues, query databases, send Slack messages, and trigger deployments. Today, nobody knows what tools any given agent can reach.
Credential Sprawl
Every agent manages its own API keys, tokens, and connection configs. Secrets are scattered across developer machines with no central management.
No Visibility
Nobody knows what tools any given agent can reach, who authorized that access, or what happened when it ran.
No Access Control
Agents get blanket access to entire services. There's no way to allow reading GitHub issues while blocking repository deletion.
No Audit Trail
When an auditor asks what your AI agents did last Tuesday, you have no answer. Actions are unrecorded and unaccountable.
No Rate Limiting or Caching
Agents hammer tool services with no throttling. Redundant calls waste tokens and compute. One runaway agent can take down a shared service for the whole organization.
Compliance & Security Risk
No traffic filtering means no redaction of sensitive data, no blocking of unsafe content, and no prompt injection mitigation. You can't demonstrate authorized, safe access to auditors.
The difference MCP Gateway makes
Go from scattered, unmanaged agent tool access to a centralized, auditable, and policy-driven control plane.
Before MCP Gateway
Centralized control
One gateway between your agents and every tool service. You set the rules. Traffic is filtered. Every action is recorded.
Agents connect to the Gateway and discover available tools
The Gateway enforces access restrictions, filters traffic, rate-limits, and routes to upstream services
Every action is logged in an immutable audit trail automatically
Works with any MCP-compatible agent
Built on the open Model Context Protocol standard. No vendor lock-in.
GitHub CopilotEverything you need to govern agent tool access
Seven integrated capabilities that give you complete control over what tools your AI agents can reach and how they perform.
Centralized Server Management
Register, import, and manage all your MCP tool services from a single control plane. Mix internal services, vendor tools, and open-source MCP servers behind one gateway — what was local and fragile becomes centralized and composable.
- Import Claude Desktop mcpServers JSON configs directly
- Mix internal, vendor, and open-source MCP servers in one place
- Support for HTTP streaming, SSE, and subprocess transports
- Enable or disable services instantly without deleting config
Kubernetes-native from the ground up
Uses Kubernetes constructs — Deployments, Services, Gateway API, NetworkPolicies, RBAC, and Secrets — to run and secure MCP servers. No external SaaS dependency.
Kubernetes Native GitOps
Deploys through standard Helm charts with ArgoCD CI/CD pipeline option. Uses K8s Deployments, Services, and Gateway API — aligns with your existing platform practices.
Flexible Storage
PostgreSQL for persistent storage with Redis for distributed caching and cross-replica coordination.
Zero-Trust Network Security
MCP servers never expose direct network ports. All access is forced through the gateway — a single choke point for NetworkPolicies, RBAC, and OAuth2/OIDC authentication. Limits lateral movement by design.
Prometheus Metrics
Native Prometheus endpoint for direct integration with your existing Grafana stack. Bearer token authentication included.
Horizontal Auto-Scaling
Handles horizontal scaling across multiple replicas with shared state. Whether you run 5 agents or 500, it scales with you.
Multi-Tenant Isolation
Every database query, cache lookup, and metrics query is scoped to the authenticated user's organization. Cross-tenant access is architecturally impossible.
Kubernetes
Prometheus
PostgreSQL
Helm
ArgoCDBuilt for enterprise scale
Advanced capabilities for organizations that need tighter integration between their AI agent infrastructure and their LLM provider strategy.
Automated Tool Injection
Link your LLM provider credentials to MCP servers or groups. When an AI agent makes a request through the LLM Gateway, tools from linked MCP services are automatically available — no manual agent configuration required.
Rate Limiting & Tool Usage Observability
Set per-agent and per-service rate limits to prevent runaway usage. Monitor tool call volumes, error rates, and latency across every agent and service — so you know exactly what's happening before it becomes a problem.
Combined LLM + MCP Governance
Unified governance across both your LLM provider access and your agent tool access. One control plane for credential management, access policies, audit trails, and cost controls across your entire AI stack.
Organization Isolation
In multi-tenant deployments, data isolation is a structural guarantee. Every database query, cache lookup, and metrics query is scoped to the authenticated user's organization. Cross-tenant access is architecturally impossible.
The MCP Gateway works alongside the Axiom LLM Gateway for unified governance across your entire AI stack. Read more about our approach to enterprise AI on the Axiom blog, or learn about the team behind the platform on our About page.