Every tool your AI uses,
approved and logged

One gateway for MCP servers, connectors, and skills, used by xpander agents, Claude, ChatGPT, Cursor, and any MCP client. You decide who gets which tools, down to a single action, and every call is recorded.

xpander Tool repo: one MCP address for Claude Desktop, ChatGPT and any MCP client, with every connector, skill and MCP server governed
xpander Tool repo: one MCP address for Claude Desktop, ChatGPT and any MCP client, with every connector, skill and MCP server governed

One URL
for every AI client

Any client that supports remote MCP servers connects to one xpander URL.

Desktop and code clients

Claude Code, Codex, Claude Desktop, Cursor, and VS Code connect to the same URL.

Cloud clients

Claude on the web and ChatGPT reach the gateway from their own cloud, so they need a URL that is reachable from the internet.

xpander agents

Agents in the Agent Runtime use the same gateway, the same tools, and the same rules.

Air-gapped? Use desktop clients and xpander agents.

What you control
from one gateway

Decide who gets which tools, down to a single action, and keep a record of every call.

One catalog

MCP servers, skills, and ready connectors to your systems, registered in one place. Turn any internal API into tools from its OpenAPI spec.

Access down to the action

Give each group only the tools it needs. An MCP server with 70 tools can show 20 to one group and all 70 to another. Hidden tools can’t be called.

Each person’s own permissions

For each tool, choose a shared service account or each person’s own sign-in, so people only reach the data they could reach anyway.

Credentials in the vault

Tokens never reach the AI client or the model.

Approvals

Sensitive actions wait for a person to approve them.

Every call recorded

Who called which tool, with what result, exported to your SIEM.

Already run MCP servers? Keep them

Keep the servers you run today, from GitHub and Jira MCP to internal, OpenAPI, and local stdio servers. xpander puts them behind one gateway, with access rules and logs.

Your MCP servers

What xpander adds

Endpoints

Your MCP servers

GitHub MCP

Jira MCP

Internal MCP servers

OpenAPI tools

Local stdio servers

What xpander adds

One URL for every client

Access down to the action

Credentials in the vault

Approvals

Every call logged

Skills registry

Skills and laptops,
governed the same way

Approved skills, managed laptops, and MCP servers wherever they run, all behind the same access rules and logs.

Skills registry

Share approved skills across agents and teams from one place, and keep private skills visible only to the people who should see them.

Only approved skills

People can’t add skills that IT hasn’t approved.

Every laptop, set up from one place

Push ready-made settings through your device management, so every AI client uses the gateway and only approved tools and skills.

Direct connections blocked

Where the client allows it, connections that skip the gateway are blocked.

Local or remote MCP servers

Run your own MCP servers next to the agent, inside its sandbox, or keep them remote behind the gateway. Either way, access rules and logs apply.

Same platform

What comes next
The rest of the platform

Add the AI Gateway for models, then the Agent Runtime and AI Workspace, on the same platform.

Every tool call,
checked against your rules

Each call is allowed, sent for approval, or blocked by the policy for that person or agent, and every decision is recorded.

Two xpander policies: contractors read Salesforce and never delete a record; no package installs and rm -rf needs approval
An xpander policy: no package installs and rm -rf needs approval

See how it would run
in your environment

Questions we hear from IT leaders

No. Your existing servers go behind the gateway.