Connect External AI Clients

If you are not taking the Skills path, or you also need to support multiple AI clients, the MCP gateway path is MCP2Skill's second main workflow.

The focus of this path is not saving Tokens, but rather:

• Configure once, reuse across multiple clients
• No need to configure MCP repeatedly in every client
• No need for each client to spin up its own MCP processes
• Better observability through a single unified entry point

What you need first

Before connecting an external client, make sure that:

• At least one MCP service is running successfully
• Or at least one workspace has been created
• You know whether you want to expose a single-service endpoint, a workspace endpoint, or the ALL endpoint

If your actual goal is "let an AI Agent reuse capabilities long term while saving as many Tokens as possible", head back to Generate and Install Skills first.

If none of this is ready yet, go back to Quick Start.

Where you can copy the configuration

In the current version, you can typically copy connection information from:

• The MCP service detail page
• The workspace detail page
• The system workspace ALL

The copy menu usually offers two options:

• Copy the endpoint URL
• Copy the JSON configuration

When to copy the endpoint URL

This is a good fit when you already understand the target client's MCP configuration format and only need the core URL.

Common uses:

• Manually entering the connection URL in an external client
• Maintaining your own, more complex client configuration
• Debugging or integration testing

When to copy the JSON configuration

This is a good fit when you want to quickly connect a Claude Code-compatible client.

This JSON typically comes pre-populated with:

• The service name
• The connection type
• The gateway URL
• The required request headers

If an API Key is enabled, the corresponding authentication header is also included in the configuration.

Why this path is still worth keeping

Even though Skills are MCP2Skill's main workflow, the gateway path remains very important because it solves a different class of problems:

• Compatible integration with different AI clients
• Smooth migration of existing client workflows
• Resource savings from unified configuration and unified runtime

Many users end up using both paths at the same time:

• The Skill path converts MCP tools into Skills that can be loaded on demand, solving Token usage and workflow efficiency
• The gateway path handles compatibility and reuse

How to choose which endpoint to copy

Single MCP service endpoint

Good for:

• Exposing only one service
• Debugging whether a specific service works correctly
• Connecting a standalone capability to a specific client

Workspace endpoint

Good for:

• Exposing a curated set of tools
• Isolating tools by project, task, or usage scenario
• Providing different tool scopes to different clients

ALL endpoint

Good for:

• Quickly checking global connectivity
• Testing whether all enabled services are visible

If you want long-term, stable usage, a custom workspace endpoint is usually still the preferred choice.

What to watch out for after enabling an API Key

Once you enable API Key authentication in the settings:

• External clients must send the correct API Key
• Copying the JSON configuration directly saves you effort
• When configuring manually, pay close attention to whether the request headers are complete

If an external client cannot connect and you just enabled an API Key, check here first.

First round of verification after connecting

Regardless of which client you connect, we recommend running a minimal verification:

1. Save or refresh the MCP configuration in the client
2. Send a request that triggers a tool call
3. Go back to MCP2Skill and check the dashboard or logs

If you can see the call record, the gateway, the client, and the tool chain are all working end to end.

If the client connects but the tools are wrong

Focus your checks on the following:

• Whether you copied the correct endpoint
• Whether some tools are disabled in the workspace
• Whether the relevant tools are turned off at the service level
• Whether the target service is currently in a connected state

Many "incomplete tools in the client" issues are not client problems at all — they are caused by filtering at the workspace or service level.

Recommended practices

• If your goal is saving Tokens, consider the Skill path first
• Use a workspace endpoint as your long-term configuration
• Use the ALL endpoint for global debugging
• When an API Key is enabled, prefer copying the JSON configuration
• After every change to a service or workspace, verify with an actual call

Related chapters

• To understand the differences between workspace endpoints, see Tool Selection and Workspace Endpoints
• To configure the port or API Key, see General and MCP Settings
• To check whether the integration works, see Logs and Diagnostics