Token sprawl across agents
Every agent holds its own credentials to every MCP server. One leak compromises the whole MCP surface.
Enterprise MCP gateway
Secure every MCP server with one governed gateway. Give each AI agent its own scoped MCP access, contain credentials at the gateway, and audit every MCP tool call without wiring agents directly to each server.
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AI agents wired directly to MCP servers fail in predictable, security-visible ways. Each one is an enterprise AI deal-blocker waiting to surface.
Every agent holds its own credentials to every MCP server. One leak compromises the whole MCP surface.
Direct MCP connections expose every tool on the server. No way to scope an agent to only what it needs.
Teams wire new agents to new MCP servers without review. Security cannot see what is reachable from where.
Direct MCP connections leave no central record of what each agent called. Incidents become reconstructions, not investigations.
Per-agent MCP permissions
Define MCP tool permissions in one place instead of minting an auth token per agent per tool. Each agent, team, or workflow gets the scoped set of tools you approve, and the gateway enforces it on every MCP tool call.
Stripe API
key held at gateway
GitHub
token held at gateway
Agent runtime
no raw credentials
MCP authentication
MCP credentials live at the gateway, not in agent prompts or code. Averta authenticates to each MCP server on the agent's behalf and scopes access per request, so a compromised agent never gives up your tokens.
Remote MCP servers
vendor tools
Self-hosted servers
your infrastructure
Custom tools
internal APIs
MCP registry
Remote MCP servers, self-hosted MCP servers, and custom tools all sit behind one Averta MCP gateway endpoint. Agents point at one governed proxy instead of a sprawl of direct MCP connections, and you version tools without touching agent code.
Protect agent workflows with end-to-end encryption, real-time redaction, and policy checks that block unsafe behavior in milliseconds while approved work keeps moving.
Define how agents handle data, tools, and decisions once. Averta applies those rules across every prompt, response, and action.
Tune policies by team, use case, customer state, risk level, and tool permission without hardcoding guardrails into every agent.
Before we started using Averta, we were hesitant to share sensitive information with agents. Averta changed that by providing the security and trust we needed, allowing us to significantly enhance our customer service experience.
Classification, policy, access control, and audit working together as one AI agent security platform, protecting your agents internally and in production.
What platform and security teams ask before they route agent tool calls through an MCP gateway
An MCP gateway is a security and governance layer that sits between AI agents and the MCP servers they use. Instead of each agent connecting directly to each MCP server with its own credentials, the gateway exposes a single governed endpoint, enforces per-agent tool permissions, holds the downstream MCP credentials, and produces an audit trail for every tool call.
A direct connection gives every agent unchecked access to every server. The gateway puts one governed point in between: approved tools only, policy before execution, result scanning, and a full audit trail. Agents get the tools they need without holding the keys to everything.
Yes. Remote MCP servers, servers you host yourself, and your own custom tools all sit behind one Averta endpoint. Agents connect to the gateway, not to each server.
Credentials for downstream tools live at the gateway, not in agent prompts or code. Averta authenticates to each connected server on the agent's behalf and scopes access per request.
Yes. Tool exposure is scoped per agent, team, or workflow. An agent only sees the tools you have approved for it, and anything else is invisible.
An LLM gateway routes model traffic. The Averta MCP Gateway governs tool execution: which tools an agent can call, whether a given call is allowed, and what the result contains. They solve different layers, and you can run both.
Checks run inline on the call path. The gateway is built to stay in front of every call without becoming the reason a workflow is slow.
Yes. The gateway sits at the tool-execution boundary, independent of model and framework. Switching models or frameworks does not change how tools are exposed or governed.
Book a demo and see how Averta OS secures your AI agents from input to execution.
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