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Version: 2026-05-26

MCP Integration

The 4C:me Safe AI Platform integrates with the Model Context Protocol (MCP), enabling AI models to access external tools and data sources.

Accessing MCP Settings​

You can access MCP configuration from the chat settings sidebar. Click the settings gear (⚙️) icon in the top-right of 4C:me, then scroll down to find the MCP configuration button.

Chat settings sidebar — MCP button

Alternatively, MCP can also be toggled from the platform Settings page:

Settings — MCP Toggle

MCP Toggle highlighted

MCP Configuration Page​

Click the MCP button to open the full MCP configuration page where you can manage your MCP server connections.

MCP Configuration

MCP Servers Page​

The MCP Servers settings page lists every server you have access to. Each row shows the server name, URL, authentication type, enabled status, authentication status, and visibility (private / public / user groups).

MCP Servers page

You can switch between grid and table views, filter the list, and search by name. Click + Create MCP Server in the top-right to add a new one.

Creating an MCP Server​

The Create MCP Server dialog captures everything needed for a new connection.

Create MCP Server dialog

Fields:

  • Name (required) — Display name for the server
  • Server URL (required) — The HTTP MCP endpoint (e.g. https://mcp.example.com/sse)
  • Description (optional) — Free-text notes
  • Authentication — See below
  • Timeout (ms) — Request timeout, default 30000 (30 seconds)
  • Email on completion — When on, sends an email when this MCP server is used and the response finishes. Useful for tools that kick off long-running server-side work
  • Visibility — Private, Public, or User Groups (see below)

The dialog has two actions at the bottom:

  • Test Connection — Probes the server with the provided URL and credentials. The check runs through the platform backend (not the browser) to avoid CORS, and reports auth or connectivity failures inline
  • Create Server — Saves the server

Authentication Types​

The Authentication dropdown supports:

  • None — For public MCP servers that don't require auth
  • Bearer token — Static token sent in the Authorization header
  • Query parameter — Token sent as a URL query parameter (e.g. ?token=...) for servers that auth via query string
  • OAuth2 — Full OAuth2 flow with PKCE support. You'll configure the client ID, authorization URL, token URL, scopes, redirect URI, and an optional token lifetime (in seconds) for cached user tokens

For OAuth2 servers, the platform handles the user authorization redirect, stores tokens server-side, and refreshes them based on the configured lifetime.

Visibility​

Each MCP server has a visibility setting:

  • Private — Only the creator can see and use the server
  • Public — Anyone in the tenant can use it (shown with a globe icon in the list)
  • User Groups — Restrict access to selected user groups (see User Management)

Example Integrations​

The MCP protocol is generic, so any compliant MCP server can be added. Two common integrations used on the platform:

SlideHub​

SlideHub provides slide and presentation generation. When connected as an MCP server, 4C:me can generate individual slides or full PowerPoint presentations directly from a chat. Ask 4C:me to "create a slide about X" or "build a presentation on Y" and the SlideHub tool calls take care of the rendering.

Typical configuration:

  • Server URL: https://ppt.slidehub.io/api/mcp/slidehub
  • Authentication: OAuth2 with the SlideHub credentials supplied by your administrator
  • Visibility: Public for tenant-wide access, or User Groups to restrict to teams with a SlideHub subscription

After saving, each user clicks the server entry to complete the OAuth flow. Until that's done, the server shows as Not Authenticated.

HubSpot​

Connecting HubSpot lets 4C:me read and write HubSpot CRM data from chat — for example, looking up contacts, listing recent deals, or summarizing pipeline activity. Use OAuth2 with the HubSpot app credentials your administrator has configured.

What Is MCP?​

The Model Context Protocol is a standard for connecting AI models to external tools, data sources, and services. MCP allows the AI to:

  • Call external tools during a conversation
  • Access data from connected services
  • Perform actions beyond pure text generation

MCP in the Platform​

Tool Call Indicator​

When the AI invokes an MCP tool during a conversation, a tool call indicator appears in the chat. This shows:

  • Which tool is being called
  • The status of the tool call
  • Results returned by the tool

Multiple MCP Servers​

The platform supports integration with multiple MCP servers, allowing connection to various external services and data sources simultaneously.

Improved Streaming​

MCP-enabled conversations feature improved response streaming:

  • Responses stream in real-time as they are generated
  • Fixed issues where responses would not stream when MCP was enabled (resolved in earlier updates)

MCP Handling​

The platform has greatly improved MCP handling with recent updates:

  • More reliable tool call execution
  • Better error handling when MCP tools fail
  • Improved integration between MCP tools and the chat interface

Authentication​

MCP servers are integrated with the platform's authentication system:

  • Secure connections to MCP servers
  • Token-based authentication for MCP tool calls
  • Proper staging and production monitoring via Sentry

Tips​

  • MCP tool calls may add slight latency to responses as external tools are invoked
  • Watch for the tool call indicator to understand when the AI is using external data
  • MCP is particularly useful for tasks that require real-time or external data