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Gumloop supports connecting to any Model Context Protocol (MCP) server. This lets you extend your agents and workflows with specialized tools, internal services, or any MCP-compatible API.
Gumloop already has 50+ pre-built MCP servers for popular services like GitHub, Slack, Notion, HubSpot, and more. These work out of the box with agents and workflows. Browse available integrations before setting up a custom server.

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Adding a Custom MCP Server

Setting up a custom MCP server takes just a few steps.
1

Go to Connectors

Navigate to Settings > Connectors and search for “MCP Server” in the available integrations.
Apps Available modal showing MCP Server option
2

Enter the Server URL

Click Add credential and enter your MCP server’s URL. The URL must use HTTPS.
MCP Server URL entry dialog
3

Configure Authentication

Fill in the server details:
MCP Server credential configuration
4

Connect

Click Connect to save your credential. The server is now available to use in your agents and workflows.
Team vs Personal credentials: Credentials can be stored at the personal level (only you can use them) or team level (shared with your team). Choose the appropriate scope when setting up. Learn more about credentials here

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Requirements

Custom MCP servers must meet these requirements:
Local MCP servers won’t work. Your server must be deployed to a publicly accessible URL. Services like Cloudflare Tunnels or ngrok can expose local servers if needed.

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Authentication Options

Gumloop supports multiple authentication methods:
  • Bearer tokens: Standard OAuth/API key authentication. When you provide an Access Token / API Key, Gumloop sends it as an Authorization: Bearer <token> header with every request to your MCP server.
  • Custom headers: For services requiring specific header formats. The Additional Header field accepts a single header in Header-Name: value format (e.g., X-API-Key: my-secret-key). This is useful for MCP servers that expect authentication in a non-standard header.
  • OAuth discovery: Automatic OAuth flow discovery (RFC 8414) for compatible servers

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Where You Can Use Custom MCP Servers

Once configured, your custom MCP servers can be used in two places: Agents and the Ask AI node.

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Using MCP Servers with Agents

Agents offer the most flexible way to use custom MCP servers. The AI can discover all available tools and use them naturally in conversation.
1

Open Agent Configuration

Go to your agent’s settings and click Add tools.
2

Select MCP Server

Choose MCP Server as the tool type and search for your configured server under the Custom tab.
Selecting a custom MCP server in agent configuration
3

Use Your Agent

Your agent now has access to all tools from the MCP server. It will automatically discover and use them based on conversation context.
Why agents are more flexible:
  • Conversational context: The agent maintains conversation history and can use tools across multiple turns
  • Automatic tool selection: The agent chooses the right tool based on your request
  • Multi-server support: Connect multiple MCP servers and let the agent orchestrate between them
  • No workflow required: Use immediately in chat, Slack, or embedded interfaces

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Using MCP Servers with Ask AI Node

For deterministic workflows, you can connect MCP servers to the Ask AI node.
1

Add Ask AI Node

Drag an Ask AI node onto your canvas.
2

Enable MCP

Click Show more options, then toggle Connect MCP Server? to ON.
3

Select Server(s)

Choose your configured MCP server(s) from the dropdown. You can select multiple servers.
Enabling MCP in Ask AI Node
When to use Ask AI node with MCP:
  • Building repeatable, production workflows
  • Need specific tool calls as part of a larger automation
  • Want to combine MCP tools with other Gumloop nodes

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Comparison: Agents vs Ask AI Node

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Model-Specific Differences

Custom MCP servers work across all models in Gumloop, but how they run depends on the provider:
  • Native MCP: The provider (OpenAI/Anthropic) connects directly to your MCP server and executes tools.
  • Backend connector (Gumloop executes tool calls): Gumloop connects to your server and presents tools as regular function calls; when invoked, Gumloop executes them and returns results to the model.

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Header Handling by Model

Anthropic models do not forward custom headers. If your MCP server relies on a custom header (e.g., X-API-Key), use the Access Token / API Key field with a Bearer token instead, or choose OpenAI, Gemini, or Groq.

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Security Considerations

Information in your prompts may be sent to your MCP server. Be mindful of sensitive data and review your server’s data handling policies.
All tools exposed by your MCP server are immediately available to the AI. There are no approval prompts before tool execution. Use appropriate authorization scopes to limit access.
When using multiple MCP servers, consider that data retrieved from one server could be passed to another. Design your prompts accordingly.

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Troubleshooting

Test with discovery first. Ask your agent or Ask AI node to “list available tools” to verify the connection is working before building complex workflows.

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Further Reading