Purogaly is the MCP gateway built for enterprise AI agents. It sits between your agents and their MCP servers, enforcing policy at the protocol layer, capturing tamper-evident evidence on every tool call, and giving operators a real-time kill switch.
The Model Context Protocol (MCP) is a JSON-RPC 2.0 protocol that defines how AI agents discover and call external tools. An MCP gateway is an enforcement layer that sits between an AI agent (the client) and the MCP servers it wants to call. Every MCP request from the agent flows through the gateway. Every response flows back through it. Nothing reaches the underlying servers without passing through.
Without a gateway, MCP traffic is point-to-point: agent talks directly to server, with no shared place to enforce policy, capture evidence, or intervene. This is fine for early prototypes. It does not scale to production enterprise environments where security, compliance, and operations teams need a single place to see and govern what agents are actually doing across all their MCP integrations.
An MCP gateway turns the protocol into a governable surface. The same place that handles authentication and routing also handles policy evaluation, audit logging, rate limiting, kill-switch enforcement, and observability. One layer, one mental model, one auditable record.
MCP is rapidly becoming the standard way enterprise AI agents access tools and data. Once you have more than a handful of agents calling more than a handful of servers, point-to-point integration stops being maintainable. Five operational problems make a gateway a requirement, not an optimization.
Without a gateway, policy lives in each agent’s code. That means policy updates require redeploying every agent. It also means a misbehaving agent can ignore the policy entirely. A gateway centralizes enforcement: policy lives in one place, applies to every agent, and cannot be bypassed.
Point-to-point MCP traffic generates per-server logs scattered across infrastructure. Reconstructing what an agent actually did, in order, across multiple tools, becomes a manual investigation. A gateway writes one chronological record of every call, in one place, hash-chained for verification.
Without a gateway, stopping a misbehaving agent depends on redeploying its code or revoking its credentials at every downstream system. That takes minutes to hours. With a gateway, you set a flag. The next request returns a denial.
A gateway gives you a real-time view of every MCP call across every agent. Anomaly detection, rate limiting, cost attribution, and capacity planning all become possible because the data is in one place rather than scattered across systems each agent talks to.
Modern AI regulations including the EU AI Act require demonstrable evidence of human oversight, traceability, and policy enforcement on autonomous AI systems. A gateway is the place that evidence comes from. Without one, the evidence is fragmented and depends on what each agent chose to log.
Purogaly\u2019s MCP gateway is a fully compatible JSON-RPC 2.0 proxy. Existing MCP clients connect to it the same way they connect to a direct MCP server. From the agent\u2019s perspective, nothing changes. From the operator\u2019s perspective, everything becomes visible and governable.
1. Authentication. The agent presents an API key. The gateway verifies it against the workspace, agent identity, and scope. Unauthenticated calls are rejected immediately.
2. Rate limiting. Per-agent and per-organization rate limits apply. Excessive request rates trigger throttling before any policy work begins.
3. Policy evaluation. The gateway evaluates the action against the active policy set in priority order, first match wins, fail-closed. Risk scoring runs in parallel against six configurable signals to produce a composite 0\u2013100 score.
4. Kill-switch check. The kill-switch state is read on every request. If active for the requesting agent, the action is denied immediately.
5. Approval check. If the policy requires human approval, the request is held as PENDING and reviewers are notified. The agent waits.
6. Forwarding. If the request passes all checks, the gateway forwards it to the target MCP server. The response is captured and returned to the agent.
7. Audit chain entry. The full record \u2014 request, policy match, decision, response \u2014 is written to a hash-chained audit log using a database advisory lock to prevent interleaving. The record is tamper-evident and independently verifiable.
Complete implementation of the MCP transport. tools/list, tools/call, prompts, resources, sampling — all governed.
Every MCP call is attributed to a specific agent. No anonymous traffic. No shared service credentials masking agent behavior.
Priority-ordered policy evaluation with first-match-wins, fail-closed semantics. Policies are versioned and updates apply on the next request.
Six configurable signals combined into a 0–100 composite score per action. Thresholds drive automatic gating decisions.
Configurable per-policy approval workflows. High-risk actions pause for human review. The reviewer and decision are captured in the chain.
Every gateway decision is written to a hash-chained log with a database advisory lock. The chain is verifiable without trusting the vendor.
Single-agent, agent-class, or organization-wide suspension. Read on every request. The next agent action returns a denial.
Server-Sent Events support for streaming MCP responses without breaking enforcement or audit.
HMAC-SHA256-signed webhooks notify downstream systems of policy decisions, approvals, and incidents.
From the agent\u2019s perspective, Purogaly\u2019s MCP gateway is just another MCP server. The agent connects to the gateway URL with an API key, and the gateway transparently routes to the underlying MCP servers configured in the workspace.
The agent calls tools/list and tools/call as it would with any MCP server. The gateway applies policy, captures evidence, enforces kill-switch state, and forwards to the underlying MCP servers configured in the workspace.
Purogaly implements the full Model Context Protocol specification. It works with any standards-compliant MCP client \u2014 Claude Desktop, Claude Code, custom-built agents, third-party agent platforms, and any other MCP client that follows the spec. It works with any standards-compliant MCP server on the other side, including community-built MCP servers and your own internal MCP implementations.
Existing MCP integrations do not need to be rewritten. The gateway sits in front of your current MCP servers, registered as the MCP endpoint your agents connect to. The agent does not know it is being governed. The MCP server does not know it is being intermediated. The operator sees and governs everything.
The gateway is infrastructure-agnostic. It runs in any cloud environment that can host an HTTPS endpoint. Customers in regulated regions deploy in-region for data residency.
An MCP gateway is an enforcement layer between AI agents (MCP clients) and the MCP servers they call. Every Model Context Protocol request flows through the gateway, which applies policy, captures audit evidence, and enforces real-time intervention controls such as kill switches before forwarding the request to the underlying server.
Direct MCP connections are fine for prototyping. Production enterprise environments need a single place to enforce policy across all agents, produce a unified audit trail, suspend misbehaving agents in real time, observe behavior at the population level, and satisfy compliance auditors. A gateway provides all five. Direct connections cannot.
Yes. Purogaly implements the full JSON-RPC 2.0 specification, including tools/list, tools/call, prompts, resources, and SSE streaming. Existing MCP clients connect with no code changes.
Purogaly’s gateway adds milliseconds of overhead for policy evaluation and audit logging. For most enterprise workflows, the added latency is imperceptible. Risk scoring runs in parallel with the rest of the evaluation to keep total time low.
Yes. Purogaly is infrastructure-agnostic. The gateway can be deployed in any cloud environment (AWS, Azure, GCP) or on-premise. Customers in regulated regions deploy in-region for data residency compliance.
Yes. The gateway operates at the MCP transport layer, which is model-agnostic. Any agent that speaks MCP — regardless of the underlying model — can be governed through the gateway.
Walk through a governed MCP call end to end. See the policy match, the audit chain entry, and the kill-switch flow.
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