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Gumloop supports connecting to any Model Context Protocol (MCP) server. This lets you extend your agents 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. 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, click the arrow next to Add Connector, and choose Add MCP Connector.
Add Connector dropdown with the Add MCP Connector option
2

Enter the Server URL

Pick a Connection type and enter your MCP server’s URL, then click Connect.
Connect MCP Server dialog with connection type and server URL
3

Configure Authentication

Gumloop probes the server and shows the Detected Auth method. If the server supports OAuth, click Authenticate and sign in to connect your account. Otherwise, open the Authentication dropdown to supply a token, API key, or custom header instead.
Configure dialog showing detected OAuth 2.0 authentication
4

Add It to Your Agent

Go back to your agent, open the Connectors section, and click Add Connector. Search for the server you just added and select it to give the agent access to its tools.
Connectors section of an agent with the Add Connector button
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.
On Enterprise? Managed Tunnels reaches MCP servers inside your network without opening inbound ports or running your own tunnel. Each becomes an organization-wide Proxied MCP rather than a personal credential.

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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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Using Custom MCP Servers with Agents

Once configured, your custom MCP servers can be added to any agent. The agent can discover all available tools and use them naturally in conversation.
1

Open Agent Configuration

Go to your agent’s settings and find the Connectors section.
2

Select MCP Server

Click Add Connector and search for your configured MCP server.
Connectors section of an agent with the Add Connector button
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.
What agents give you:
  • 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
  • Available everywhere: Use immediately in chat, Slack, or embedded pages

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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 to “list available tools” to verify the connection is working before relying on it.

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Further Reading