AIAI Weather Agent (With HTTP request)
AI agent that retrieves live weather data via API.
Build and host an MCP server in Latenode, then link Claude for Desktop, your editor, and other AI clients to data, APIs, and internal flows. Add MCP Trigger, define actions as branches, return clean outputs with MCP Response, and go live without Docker or extra infrastructure.
Free plan available·No credit card·Hosted by Latenode
Without one shared endpoint, each assistant needs its own connector to each client, database, and service. Latenode turns one scenario into an MCP server so Claude, your editor, and other AI tools can discover and use the same capabilities.
Custom integrations pile up when every AI client needs its own connection to every app.
Manual deployment, gateway setup, and debugging slow down teams trying to add a new model or assistant.
One hosted MCP server can expose many actions, branches, and routes through a single URL.
MCP Trigger, built-in auth, and MCP Response help teams move from test to production in hours, not sprints.
Latenode MCP server lets you add action names, descriptions, parameters, auth, and custom logic in a visual builder. Then you connect Claude for Desktop, ChatGPT-compatible setups, or your own assistant to the same server URL.
Get startedOne hosted workflow can cover setup, client onboarding, action use, auth, and debugging in a single operational flow.
MCP Trigger turns your scenario into an MCP server. Each branch becomes a separate action that any MCP-compatible assistant can discover. You configure description, version, auth, and inputs in one place, then copy the URL and link your AI client.
Add MCP Trigger to a new scenario, set the description and version label, and copy the URL. Every directly attached branch becomes an action, so your assistant can list, choose, and call tasks through one endpoint.
Turn on a key in MCP Trigger when the endpoint should not be public. The same setup stays easy to use while still enforcing permissions, making it safer to expose internal data, production systems, or company instructions to a hosted client.
Instead of sending raw HTTP bodies, headers, and log data back to the assistant, use MCP Response to shape a clean payload. That gives the client just the result it needs and improves action reliability in Claude and other MCP clients.
Your setup is not limited to one action type. Add 5,500+ apps, custom endpoint calls, JavaScript, loops, conditions, or AI-generated code in the same branch. This makes it practical to build real assistant workflows instead of isolated demos.
Use a simple echo action, sample input parameters, and fast branches to check discovery and outputs before onboarding your assistant. Clear descriptions, predictable parameter names, and structured responses make debugging much easier later.
Once your MCP server is live, setup is simple: add a new endpoint or connector, paste the URL, provide the key if auth is enabled, and confirm your actions appear. That shared flow works across Claude for Desktop and many assistant setups.
In Cursor, open Settings, find MCP or MCPs / Tools, add a server, paste your Latenode Server URL, then add the key if prompted. Save and open the tools list to verify the MCP tools are visible and callable.
In Claude for Desktop, open Settings, go to Connectors, click Add custom connector, paste the Latenode URL, and provide the key if required. Save the configuration and enable the connector and verify Claude can reach your hosted server.
If your ChatGPT environment supports MCP directly or through a bridge, the flow is the same: open Connectors or Tools settings, add a new server, paste the URL, provide credentials, and confirm the list loads correctly.
For OpenAI or assistant environments that sit behind middleware, add the same URL there, configure the key if needed, and run a quick prompt to verify discovery and action execution. One server supports many surfaces.
Because Latenode hosts the server, teams can use a URL-based setup instead of managing local processes, stdio wrappers, or a custom adapter. That is useful when multiple assistants, editors, or shared tools need shared use of the same actions and configuration.
An MCP server is only useful when the actions behind it are practical. Latenode lets you use databases, docs, HTTP endpoints, CRM data, and JavaScript logic, then register each branch with a clear name and instruction set so the client knows when to call it.
HubSpot, Slack, Google Sheets, GitHub, Jira, Airtable, Salesforce, and many other apps can become callable actions. That means your assistant can work with the same systems your team already trusts, instead of being limited to toy examples.
Use PostgreSQL, Airtable, Google Sheets, or other sources to return live context to the assistant. The client sees a single action interface, but your server can combine multiple sources, transform results, and shape the response before the data reaches the user.
Use endpoint nodes or custom HTTP requests when you need a server-like action that is not available as a native app. Your server can call REST endpoints, normalize results, and expose the final operation as one clean action with precise parameter descriptions.
When your server needs transformations, validation, custom schemas, or complex orchestration, add JavaScript directly in the flow. This keeps the main configuration approachable while still giving teams room for advanced logic.
A single action can do more than read data. It can validate input, branch by condition, call multiple apps, write to systems, and return a concise answer. That is what makes hosted MCP useful for real assistant automation instead of isolated demos.
Configure clients, define safety boundaries, and fix the most common reasons actions do not appear in the assistant. Test with a simple echo action first, then connect your AI client once discovery works reliably.
Use clear action names, descriptive parameter keys, and short but specific descriptions. That helps the client understand when the action should be used and what input format it expects, which improves behavior in assistants like Claude.
First check that Tool Name is set on the node directly attached to MCP Trigger. Then verify that you copied the correct URL and that the client is sending credentials when required. If the connection drops, keep execution fast and return only what you need.
Because Latenode hosts the endpoint, teams can use a hosted configuration instead of wiring local stdio processes on every device. This is especially helpful for shared actions, hosted assistants, and setups that need a stable URL.
Auth in MCP Trigger lets you decide whether the server is open for test usage or protected with a key. That matters when the server reaches sensitive data, internal entities, or write actions where permission and traceability are part of the trust model.
If auth errors appear, verify whether auth is enabled or disabled as expected and update the key in the client. If results are too large or slow, reduce payload size with MCP Response and keep branches focused. That is often enough to solve the most common limit in early MCP rollouts.
Follow the actual Latenode flow: MCP Trigger, action branches, MCP Response, and client setup.
Create a new scenario, add MCP Trigger, and configure description, version, URL, and optional auth.
Each node attached directly to MCP Trigger becomes an action. Add names, descriptions, and fromMCP parameters so the client can call them correctly.
Shape the output, hide internal fields, and return only the final context the assistant needs to complete the task.
Copy the URL into Claude for Desktop or another MCP client, add the key if required, and verify your actions are listed.
Search the apps, data sources, and client categories teams most often use through hosted actions.
Use the code node, HTTP requests, or a custom app integration when the standard catalog is not enough for your use case.
Start from practical examples for CRM access, live data, design systems, and internal operations.
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| Feature | Latenode MCP server | Manual setup | Automation platforms without native MCP |
|---|---|---|---|
| Native MCP support | MCP Trigger + hosted server | DIY implementation | Limited / indirect |
| Deployment | Hosted by default | Docker, cloud, config | Usually not a real hosted endpoint |
| Tool creation | Each branch becomes an action | Hand-written schemas and routing | Automation actions only |
| Response shaping | MCP Response node | Custom code | Limited |
| Apps | 5,500+ apps | Build each connector | Varies |
| AI coverage | 400+ AI engines included | Bring your own stack | Varies by plan |
| Auth | Key auth in MCP Trigger | Manual implementation | Inconsistent |
| Time to first test | Minutes to hours | Days to weeks | Not built for MCP |
If your current setup uses web automation, custom scripts, and one-off connectors for each assistant, standardizing on MCP can simplify the stack.
Product page, MCP nodes documentation, and setup instructions for Claude for Desktop, Cursor, and other MCP clients.
A hosted server exposes actions and context to an MCP-compatible client or assistant through a standard protocol, so you do not need to build separate connectors for every client and every action.
Create the scenario, copy the URL from MCP Trigger, add a new server in Claude for Desktop or your editor settings, and provide the key if auth is enabled.
Check that Tool Name is set on the node directly attached to MCP Trigger, confirm you copied the right URL, and verify the client is sending the expected credentials.
Yes. Each action branch can use apps, databases, requests, conditions, loops, and JavaScript, then return a structured response through MCP Response.
Latenode hosts the MCP server, so you can use a remote URL-based setup instead of managing local stdio processes for every user or device.
Create a hosted server, use Claude for Desktop and an editor, shape clean responses, and control auth from one Latenode workflow.