MCP Servers

Connect external Model Context Protocol (MCP) servers to your Workspace and expose their tools to your AI Agents.

The Model Context Protocol (MCP) is an open standard that lets AI applications connect to external tools and services through a uniform interface. By configuring MCP servers in indigo.ai, you give your AI Agents access to tools hosted outside the platform — for example, third-party search providers, internal knowledge services, or custom integrations exposed by your team — without writing custom API blocks for every endpoint.

Once an MCP server is connected, its tools become available inside the Agent Block just like any native integration.

Looking for general guidance on connecting external systems? Start from the Tools page for a wider overview of how indigo.ai integrates with third-party APIs.

1. Add a new MCP Server

From your Workspace, open Agent Settings → Integrations. This is the section where you manage Tool Collections and MCP Servers. Click Add MCP Server to open the configuration window.

Add MCP Server window in Agent Settings → Integrations.

Fill in the following fields:

• Name — A short identifier for the server (e.g. the service name).

• Server description (optional) — A free-text description that helps you remember what this server is for.

• Connection — The URL of the MCP endpoint to connect to (e.g. https://mcp.example.com). The URL must not contain the transport-specific path (e.g. /mcp); use only the base URL as shown in the example.

• Headers (optional) — Add custom HTTP headers as Key / Value pairs if the server requires authentication or signed requests. Click + Add secret to insert sensitive values (tokens, API keys) using workspace secrets — they are stored encrypted and resolved server-side at runtime.

When all required fields are filled, click Save. The platform automatically attempts to connect to the server.

2. Connection status

After saving, the connection state is displayed in the server's edit window and can take one of three values:

State	Meaning
🟢 Connected	The connection succeeded. The server's tools are available to your Agents.
🔴 Connection failed	The connection attempt failed. Verify the URL and any authentication headers.
⚪ Not connected	No connection attempt has been made yet.

Connection status shown in the MCP Server edit window.

If a server is temporarily unreachable, indigo.ai automatically attempts to reconnect the next time one of its tools is invoked, so transient outages do not require manual intervention.

3. Edit, reconnect, or delete a server

To change a previously configured MCP server, select it from the list to open the Edit window. From there you can:

• Update name, description, URL, or headers.

• Reconnect — Force a new connection attempt and refresh the list of available tools. Useful when the server has added new tools or when the connection has dropped.

• Delete — Remove the MCP server from the Workspace.

Remember to click Save after any change.

4. Use MCP tools in an Agent Block

Once an MCP server is connected and its tools are loaded, you can enable them inside any Agent Block of your Workspace:

1. Open the Agent Block where you want the tools to be available.

2. Go to the Integrations tab.

3. In the Choose integration dropdown, select the MCP server you configured.

4. In the Choose tool dropdown, you'll see the list of tools exposed by that server.

The "Choose tool" dropdown showing the MCP tools exposed by the selected server.

1. Tick the checkbox next to each tool you want to make available to that Agent.

One MCP tool selected for use in this Agent Block.

The selected tools are now callable by the Agent during conversations. As with native tools, the Agent decides at runtime which tool to invoke based on the user's intent and the conversation context — you don't need to define rigid workflows in advance. See Tools — Multi-tool orchestration for details on how the platform handles multiple tool calls in a single turn.