Integration
Connect BigML to Geckoboard
When New project fires in BigML, your agent runs Append Dataset Data in Geckoboard. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want BigML and Geckoboard to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)BigML holds the projects, datasets and models your team builds; Geckoboard holds the screen everyone looks at. Joining them means a new project in BigML can pull its sources, datasets or models and push them straight into a Geckoboard dataset, so the board on the wall reflects what is actually in the modelling account without anyone copying rows by hand.
Example flows
What BigML can start in Geckoboard
When New project in BigML
then Append Dataset Data in Geckoboard
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with BigML and Geckoboard
Triggers and actions 1 trigger · 9 actions
- New project
Triggered when a new project is created in BigML. Polls the BigML projects list endpoint and emits each project, deduplicated by its resource id.
- Get Resource Status
Retrieve a BigML resource by id (source/dataset/model/prediction) to poll its status and read results.
- List Datasets
List BigML datasets, optionally filtered/paginated.
- List Models
List BigML models, optionally filtered/paginated.
- List Sources
List BigML sources, optionally filtered/paginated.
- Append Dataset Data
Appends records to a dataset, keeping the most recent rows.
- Create or Update Dataset
Creates a new dataset or updates the schema of an existing one.
- Delete Dataset
Deletes a dataset and all of its data.
- Replace Dataset Data
Replaces all data in a dataset with the provided records.
- Verify API Key
Verifies the Geckoboard API key by hitting the root endpoint. Read-only.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
What our customers say
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Questions
BigML and Geckoboard, answered
Can something happening in Geckoboard start a workflow?
No. Geckoboard offers actions here, such as creating a dataset, appending rows, replacing data or deleting a dataset, but no triggers. Every scenario on this page starts from the New project trigger in BigML and then writes into Geckoboard.
Should I append rows or replace the dataset data?
Append adds records to the Geckoboard dataset and keeps the most recent rows, which suits a running log of projects. Replace swaps out everything with the records from the current run, which suits a board that should show the current list of models or datasets.
What can start an automation from BigML?
Any of BigML's 1 trigger in the catalog, including New project. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Geckoboard when something happens in BigML?
Any of Geckoboard's 5 actions, including Append Dataset Data, Create or Update Dataset, Delete Dataset and Verify API Key. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Geckoboard to BigML?
Geckoboard has no triggers in the catalog today, so automations start in BigML. If you need the other direction, ask: your agent reads Geckoboard's API documentation and adds it.
Do I have to build a connector for BigML or Geckoboard?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
Can my AI client use BigML and Geckoboard without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.