Integration
Connect Leiga to ScraperAPI
When Updated Issue fires in Leiga, your agent runs Add DataPipeline project in ScraperAPI. 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 Leiga and ScraperAPI to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiAny 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)Example flows
What Leiga can start in ScraperAPI
When Updated Issue in Leiga
then Add DataPipeline project in ScraperAPI
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 Leiga and ScraperAPI
Triggers and actions 1 trigger · 25 actions
- Updated Issue
Triggers when an issue is updated in Leiga.
- Add comment
Adds a comment to a Leiga issue or other record, optionally as a reply to an existing comment.
- Add epic
Creates a new epic in a Leiga project.
- Add project
Creates a new project in Leiga from a project template, with a name, leader and optional description.
- Add version
Creates a new version (release) in Leiga with a name, owner, and optional description, start date and estimated release date.
- Create Issue
Creates a new issue in a Leiga project with the issue type and field values you provide.
- Delete issue
Deletes an issue from a Leiga project.
- Find issues by criteria
Searches the issues in a Leiga project matching a summary keyword, status types, field values or date ranges, and returns the matching issues.
- Get issue
Returns the full details of a Leiga issue, including its custom field values, by issue ID.
- Get project
Returns the details of a Leiga project by its ID.
- Get version
Returns the details of a Leiga version, including its name, status and release dates.
- List comments
Returns the comments on a Leiga issue or other item, including replies and attachments.
- List Issue Types
Returns the issue types (such as bug or task) available in a Leiga project.
- List projects
Returns all projects in your Leiga organization with their id, name, key and archived status.
- Update issue
Updates an existing Leiga issue's field values, such as its summary, description, status, priority, assignee or labels.
- Update project
Updates a Leiga project's overview fields, such as its name or start time.
- Add async scrape job
Submit an asynchronous scraping job.
- Add async scrape jobs in batch
Submit many URLs as async jobs in one call.
- Add DataPipeline project
Create a DataPipeline project with input list, schedule and settings.
- Cancel Crawler Job
Cancel an active crawler job by its job ID.
- Create Crawler Job
Start a one-off crawler job that follows links from a starting URL and streams page results to a webhook.
- Delete DataPipeline project
Archive a DataPipeline project.
- Extract Data From URL
Extract data from a URL — HTML, Markdown, plain text, or parsed JSON. Handles proxies, browser rendering, and CAPTCHAs.
- Get account usage
Return plan limits, request counts, failed request count and concurrent requests.
- Get Structured Data
Retrieve parsed data from supported source categories. Choose a category and operation to get clean JSON.
- Update DataPipeline project
Edit a DataPipeline project's settings/schedule/input.
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
Leiga and ScraperAPI, answered
What can start an automation from Leiga?
Any of Leiga's 1 trigger in the catalog, including Updated Issue. Describe the moment in plain language and your agent picks the right one.
What can your agent do in ScraperAPI when something happens in Leiga?
Any of ScraperAPI's 10 actions, including Create Crawler Job, Update DataPipeline project, Add async scrape job and Add async scrape jobs in batch. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from ScraperAPI to Leiga?
ScraperAPI has no triggers in the catalog today, so automations start in Leiga. If you need the other direction, ask: your agent reads ScraperAPI's API documentation and adds it.
Do I have to build a connector for Leiga or ScraperAPI?
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.
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.