# Linear Integrations Scraper (`crawlerbros/linear-integrations-scraper`) Actor Scrape Linear's integration directory - browse all 60+ integrations or fetch specific ones by slug. Extracts name, description, categories, developer, logoUrl, docsUrl, featureFlags and more. - **URL**: https://apify.com/crawlerbros/linear-integrations-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Developer tools, Integrations, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Linear Integrations Scraper Scrape **Linear's integration directory** at [linear.app/integrations](https://linear.app/integrations). Extract details for all 60+ integrations including name, categories, developer info, logo, documentation links, and feature flags (OAuth, webhook, API, SSO, MCP). ### What you get Each record includes: | Field | Description | |---|---| | `slug` | Integration URL slug (e.g. `github`, `slack`) | | `name` | Display name | | `description` | Short description of the integration | | `categories` | List of categories (e.g. `["Essentials", "Engineering"]`) | | `developer` | `{name, url}` of the integration developer | | `logoUrl` | Integration logo image URL | | `docsUrl` | Link to Linear's documentation for this integration | | `integrationUrl` | Link to Linear's settings page for this integration | | `sourceUrl` | Canonical URL of the integration page | | `featureFlags` | `{oauth, webhook, api, sso, mcp}` boolean flags | | `recordType` | Always `integration` | | `scrapedAt` | UTC ISO timestamp | ### Input | Field | Type | Required | Description | |---|---|---|---| | `mode` | select | Yes | `browse` — all integrations; `getBySlug` — specific integrations by slug | | `category` | select | No | Filter by category (e.g. `Engineering`, `Automations`) | | `slugs` | array | No | Slug list for `getBySlug` mode (e.g. `["github", "slack"]`) | | `maxItems` | integer | No | Max records to emit (default: 100, max: 10000) | #### Modes **`browse`** — Discovers all integrations from the index page and fetches each one. Optionally filter by `category`. **`getBySlug`** — Fetches specific integrations by their URL slug. Provide a `slugs` array. ### Examples #### Browse all integrations ```json { "mode": "browse", "maxItems": 50 } ```` #### Get specific integrations ```json { "mode": "getBySlug", "slugs": ["github", "slack", "figma", "sentry"], "maxItems": 10 } ``` #### Browse only AI/Agent integrations ```json { "mode": "browse", "category": "Agents", "maxItems": 20 } ``` ### Sample output ```json { "slug": "github", "name": "GitHub", "description": "Connect GitHub to automate PR workflows, review code in Linear, sync issues and understand your codebase.", "categories": ["Essentials", "Engineering", "Linear crafted"], "developer": { "name": "Linear", "url": "https://github.com" }, "logoUrl": "https://webassets.linear.app/images/ornj730p/production/c6a06d2d2349df613faf9de2879142b1e60e59ec-640x640.png", "docsUrl": "https://linear.app/docs/github-integration", "integrationUrl": "https://linear.app/settings/integrations/github", "sourceUrl": "https://linear.app/integrations/github", "featureFlags": { "oauth": true, "webhook": true, "api": true }, "recordType": "integration", "scrapedAt": "2026-05-30T12:00:00+00:00" } ``` ### Use cases - **Integration audits**: Catalog all tools that integrate with Linear for vendor assessments - **Competitor analysis**: Track which tools build native Linear integrations - **Developer research**: Find integrations that support specific protocols (OAuth, webhooks, API) - **Category exploration**: Discover all automation, analytics, or security integrations for Linear - **Directory building**: Maintain an up-to-date index of the Linear integration ecosystem ### Integration categories Linear organizes integrations into 12 categories: - **Essentials** — Core productivity tools (GitHub, Slack, Figma) - **Agents** — AI coding agents (Cursor, Devin, GitHub Copilot) - **AI clients** — AI chat interfaces with Linear support - **Engineering** — Development tools (VS Code, Sentry, Datadog) - **Linear crafted** — Integrations built and maintained by Linear - **Bug Reporting** — Issue capture tools - **Automations** — Workflow automation (Zapier, Jira sync) - **Customer Experience** — Support tools (Zendesk, Intercom, Front) - **Security & Compliance** — Security platforms (Vanta, Drata) - **Analytics** — Data integration (Airbyte, Fivetran, Google Sheets) - **Collaboration** — Team tools (Notion, Microsoft Teams, Discord) - **Media & Design** — Design tools (Figma, Miro, Loom) ### FAQ **Does this require a Linear account?** No. All integration listing pages are publicly accessible without authentication. **How many integrations does Linear have?** Linear currently lists 60+ integrations across 12 categories. New integrations are added regularly. **What are feature flags?** The scraper detects mentions of integration capabilities: `oauth` (authorization flow), `webhook` (event-based triggers), `api` (REST/GraphQL access), `sso` (single sign-on / SAML), `mcp` (Model Context Protocol for AI agents). **Can I filter by multiple categories?** Currently one category filter is supported per run. Run multiple times with different categories to collect all. **What is the `sourceUrl` field?** The canonical URL of the integration's page on linear.app (e.g. `https://linear.app/integrations/github`). # Actor input Schema ## `mode` (type: `string`): What to fetch. 'browse' (or 'search') returns all integrations optionally filtered by category/query. 'getBySlug' fetches specific integrations by their slug. ## `category` (type: `string`): Filter results to a specific integration category (mode=browse only). ## `slugs` (type: `array`): List of integration slugs to fetch (e.g. 'github', 'slack', 'figma'). Used when mode=getBySlug. ## `maxItems` (type: `integer`): Maximum number of integration records to emit. ## Actor input object example ```json { "mode": "browse", "category": "", "slugs": [], "maxItems": 100 } ``` # Actor output Schema ## `integrations` (type: `string`): Dataset containing all scraped Linear integrations. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "mode": "browse", "category": "", "slugs": [], "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/linear-integrations-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "mode": "browse", "category": "", "slugs": [], "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/linear-integrations-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "mode": "browse", "category": "", "slugs": [], "maxItems": 100 }' | apify call crawlerbros/linear-integrations-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/linear-integrations-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linear Integrations Scraper", "description": "Scrape Linear's integration directory - browse all 60+ integrations or fetch specific ones by slug. Extracts name, description, categories, developer, logoUrl, docsUrl, featureFlags and more.", "version": "1.0", "x-build-id": "SRqHdlPwLwTjtdeo9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~linear-integrations-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-linear-integrations-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~linear-integrations-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-linear-integrations-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~linear-integrations-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-linear-integrations-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "browse", "search", "getBySlug" ], "type": "string", "description": "What to fetch. 'browse' (or 'search') returns all integrations optionally filtered by category/query. 'getBySlug' fetches specific integrations by their slug.", "default": "browse" }, "category": { "title": "Category filter", "enum": [ "", "Essentials", "Agents", "AI clients", "Engineering", "Linear crafted", "Bug Reporting", "Automations", "Customer Experience", "Security & Compliance", "Analytics", "Collaboration", "Media & Design" ], "type": "string", "description": "Filter results to a specific integration category (mode=browse only).", "default": "" }, "slugs": { "title": "Integration slugs (mode=getBySlug)", "type": "array", "description": "List of integration slugs to fetch (e.g. 'github', 'slack', 'figma'). Used when mode=getBySlug.", "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of integration records to emit.", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```