Feat: Strands core Apify tools

README.md

@@ -99,6 +99,8 @@ Below is a comprehensive table of all available tools, how to use them with an a
 | Tool | Agent Usage | Use Case |
 |------|-------------|----------|
 | a2a_client | `provider = A2AClientToolProvider(known_agent_urls=["http://localhost:9000"]); agent = Agent(tools=provider.tools)` | Discover and communicate with A2A-compliant agents, send messages between agents |
+| apify_run_actor | `agent.tool.apify_run_actor(actor_id="apify/website-content-crawler", run_input={"startUrls": [{"url": "https://example.com"}]})` | Run any Apify Actor with arbitrary input |
+| apify_scrape_url | `agent.tool.apify_scrape_url(url="https://example.com")` | Scrape a URL and return its content as markdown |
 | file_read | `agent.tool.file_read(path="path/to/file.txt")` | Reading configuration files, parsing code files, loading datasets |
 | file_write | `agent.tool.file_write(path="path/to/file.txt", content="file content")` | Writing results to files, creating new files, saving output data |
 | editor | `agent.tool.editor(command="view", path="path/to/file.py")` | Advanced file operations like syntax highlighting, pattern replacement, and multi-file edits |
@@ -960,6 +962,47 @@ result = agent.tool.mongodb_memory(
 )
 ```
 
+### Apify
+
+```python
+from strands import Agent
+from strands_tools.apify import APIFY_CORE_TOOLS
+
+agent = Agent(tools=APIFY_CORE_TOOLS)
+
+# Scrape a single URL and get Markdown content
+content = agent.tool.apify_scrape_url(url="https://example.com")
+
+# Run an Actor and get results in one step
+result = agent.tool.apify_run_actor_and_get_dataset(
+    actor_id="apify/website-content-crawler",
+    run_input={"startUrls": [{"url": "https://example.com"}]},
+    dataset_items_limit=50,
+)
+
+# Run a saved task (pre-configured Actor with default inputs)
+run_info = agent.tool.apify_run_task(task_id="user/my-task")
+
+# Run a task and get results in one step
+result = agent.tool.apify_run_task_and_get_dataset(
+    task_id="user/my-task",
+    task_input={"query": "override default input"},
+    dataset_items_limit=50,
+)
+
+# Run an Actor (get metadata only)
+run_info = agent.tool.apify_run_actor(
+    actor_id="apify/google-search-scraper",
+    run_input={"queries": "AI agent frameworks"},
+)
+
+# Fetch dataset items separately
+items = agent.tool.apify_get_dataset_items(
+    dataset_id="abc123",
+    limit=100,
+)
+```
+
 ## 🌍 Environment Variables Configuration
 
 Agents Tools provides extensive customization through environment variables. This allows you to configure tool behavior without modifying code, making it ideal for different environments (development, testing, production).
@@ -1068,6 +1111,12 @@ The Mem0 Memory Tool supports three different backend configurations:
 - If `NEPTUNE_ANALYTICS_GRAPH_IDENTIFIER` is set, the tool will configure Neptune Analytics as graph store to enhance memory search
 - LLM configuration applies to all backend modes and allows customization of the language model used for memory processing
 
+#### Apify Tool
+
+| Environment Variable | Description | Default |
+|----------------------|-------------|---------|
+| APIFY_API_TOKEN | Apify API token for authentication (required) | None |
+
 #### Bright Data Tool
 
 | Environment Variable | Description | Default |

docs/apify_tool.md

@@ -0,0 +1,205 @@
+# Apify
+
+The Apify tools (`apify.py`) enable [Strands Agents](https://strandsagents.com/) to interact with the [Apify](https://apify.com) platform — running any [Actor](https://apify.com/store) or [task](https://docs.apify.com/platform/actors/running/tasks) by ID, fetching dataset results, and scraping individual URLs.
+
+## Installation
+
+```bash
+pip install strands-agents-tools[apify]
+```
+
+## Configuration
+
+Set your Apify API token as an environment variable:
+
+```bash
+export APIFY_API_TOKEN=apify_api_your_token_here
+```
+
+Get your token from [Apify Console](https://console.apify.com/account/integrations) → Settings → API & Integrations → Personal API tokens.
+
+## Usage
+
+Register all core tools at once:
+
+```python
+from strands import Agent
+from strands_tools.apify import APIFY_CORE_TOOLS
+
+agent = Agent(tools=APIFY_CORE_TOOLS)
+```
+
+Or pick individual tools:
+
+```python
+from strands import Agent
+from strands_tools import apify
+
+agent = Agent(tools=[
+    apify.apify_run_actor,
+    apify.apify_scrape_url,
+])
+```
+
+### Scrape a URL
+
+The simplest way to extract content from any web page. Uses the [Website Content Crawler](https://apify.com/apify/website-content-crawler) Actor under the hood and returns the page content as Markdown:
+
+```python
+content = agent.tool.apify_scrape_url(url="https://example.com")
+```
+
+### Run an Actor
+
+Execute any Actor from [Apify Store](https://apify.com/store) by its ID. The call blocks until the Actor run finishes or the timeout is reached:
+
+```python
+result = agent.tool.apify_run_actor(
+    actor_id="apify/website-content-crawler",
+    run_input={"startUrls": [{"url": "https://example.com"}]},
+    timeout_secs=300,
+)
+```
+
+The result is a JSON string containing run metadata: `run_id`, `status`, `dataset_id`, `started_at`, and `finished_at`.
+
+### Run an Actor and Get Results
+
+Combine running an Actor and fetching its dataset results in a single call:
+
+```python
+result = agent.tool.apify_run_actor_and_get_dataset(
+    actor_id="apify/website-content-crawler",
+    run_input={"startUrls": [{"url": "https://example.com"}]},
+    dataset_items_limit=50,
+)
+```
+
+### Run a task
+
+Execute a saved [Actor task](https://docs.apify.com/platform/actors/running/tasks) — a pre-configured Actor with preset inputs. Use this when a task has already been set up in Apify Console:
+
+```python
+result = agent.tool.apify_run_task(
+    task_id="user~my-task",
+    task_input={"query": "override input"},
+    timeout_secs=300,
+)
+```
+
+The result is a JSON string containing run metadata: `run_id`, `status`, `dataset_id`, `started_at`, and `finished_at`.
+
+### Run a task and get results
+
+Combine running a task and fetching its dataset results in a single call:
+
+```python
+result = agent.tool.apify_run_task_and_get_dataset(
+    task_id="user~my-task",
+    dataset_items_limit=50,
+)
+```
+
+### Fetch dataset items
+
+Retrieve results from a dataset by its ID. Useful after running an Actor to get the structured results separately, or to access any existing dataset:
+
+```python
+items = agent.tool.apify_get_dataset_items(
+    dataset_id="abc123",
+    limit=100,
+    offset=0,
+)
+```
+
+## Tool Parameters
+
+### apify_scrape_url
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `url` | string | Yes | — | The URL to scrape |
+| `timeout_secs` | int | No | 120 | Maximum time in seconds to wait for scraping to finish |
+| `crawler_type` | string | No | `"cheerio"` | Crawler engine to use. One of `"cheerio"` (fastest, no JS rendering), `"playwright:adaptive"` (fast, renders JS if present), or `"playwright:firefox"` (reliable, renders JS, best at avoiding blocking but slower) |
+
+**Returns:** Markdown content of the scraped page as a plain string.
+
+### apify_run_actor
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `actor_id` | string | Yes | — | Actor identifier (e.g., `apify/website-content-crawler`) |
+| `run_input` | dict | No | None | JSON-serializable input for the Actor |
+| `timeout_secs` | int | No | 300 | Maximum time in seconds to wait for the Actor run to finish |
+| `memory_mbytes` | int | No | None | Memory allocation in MB for the Actor run (uses Actor default if not set) |
+| `build` | string | No | None | Actor build tag or number to run a specific version (uses latest build if not set) |
+
+**Returns:** JSON string with run metadata: `run_id`, `status`, `dataset_id`, `started_at`, `finished_at`.
+
+### apify_run_task
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `task_id` | string | Yes | — | Task identifier (e.g., `user~my-task` or a task ID) |
+| `task_input` | dict | No | None | JSON-serializable input to override the task's default input |
+| `timeout_secs` | int | No | 300 | Maximum time in seconds to wait for the task run to finish |
+| `memory_mbytes` | int | No | None | Memory allocation in MB for the task run (uses task default if not set) |
+
+**Returns:** JSON string with run metadata: `run_id`, `status`, `dataset_id`, `started_at`, `finished_at`.
+
+### apify_run_task_and_get_dataset
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `task_id` | string | Yes | — | Task identifier (e.g., `user~my-task` or a task ID) |
+| `task_input` | dict | No | None | JSON-serializable input to override the task's default input |
+| `timeout_secs` | int | No | 300 | Maximum time in seconds to wait for the task run to finish |
+| `memory_mbytes` | int | No | None | Memory allocation in MB for the task run (uses task default if not set) |
+| `dataset_items_limit` | int | No | 100 | Maximum number of dataset items to return |
+| `dataset_items_offset` | int | No | 0 | Number of dataset items to skip for pagination |
+
+**Returns:** JSON string with run metadata plus an `items` array containing the dataset results.
+
+### apify_get_dataset_items
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `dataset_id` | string | Yes | — | The Apify dataset ID to fetch items from |
+| `limit` | int | No | 100 | Maximum number of items to return |
+| `offset` | int | No | 0 | Number of items to skip for pagination |
+
+**Returns:** JSON string containing an array of dataset items.
+
+### apify_run_actor_and_get_dataset
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `actor_id` | string | Yes | — | Actor identifier (e.g., `apify/website-content-crawler`) |
+| `run_input` | dict | No | None | JSON-serializable input for the Actor |
+| `timeout_secs` | int | No | 300 | Maximum time in seconds to wait for the Actor run to finish |
+| `memory_mbytes` | int | No | None | Memory allocation in MB for the Actor run (uses Actor default if not set) |
+| `build` | string | No | None | Actor build tag or number to run a specific version (uses latest build if not set) |
+| `dataset_items_limit` | int | No | 100 | Maximum number of dataset items to return |
+| `dataset_items_offset` | int | No | 0 | Number of dataset items to skip for pagination |
+
+**Returns:** JSON string with run metadata plus an `items` array containing the dataset results.
+
+## Troubleshooting
+
+| Error | Cause | Fix |
+|-------|-------|-----|
+| `APIFY_API_TOKEN environment variable is not set` | Token not configured | Set the `APIFY_API_TOKEN` environment variable |
+| `apify-client package is required` | Optional dependency not installed | Run `pip install strands-agents-tools[apify]` |
+| `Actor ... finished with status FAILED` | Actor execution error | Check Actor input parameters and run logs in [Apify Console](https://console.apify.com) |
+| `Task ... finished with status FAILED` | Task execution error | Check task configuration and run logs in [Apify Console](https://console.apify.com) |
+| `Actor/task ... finished with status TIMED-OUT` | Timeout too short for the workload | Increase the `timeout_secs` parameter |
+| `Task ... returned no run data` | Task `call()` returned `None` (wait timeout) | Increase the `timeout_secs` parameter |
+| `No content returned for URL` | Website Content Crawler returned empty results | Verify the URL is accessible and returns content |
+
+## References
+
+- [Strands Agents Tools](https://strandsagents.com/latest/user-guide/concepts/tools/tools_overview/)
+- [Apify Platform](https://apify.com)
+- [Apify API Documentation](https://docs.apify.com/api/v2)
+- [Apify Store](https://apify.com/store)
+- [Apify Python Client](https://docs.apify.com/api/client/python/docs)

pyproject.toml

@@ -61,6 +61,9 @@ Homepage = "https://github.com/strands-agents/tools"
 Documentation = "https://strandsagents.com/"
 
 [project.optional-dependencies]
+apify = [
+    "apify-client>=2.5.0,<3.0.0",
+]
 build = [
     "hatch>=1.16.5",
 ]
@@ -122,7 +125,7 @@ mongodb-memory = [
 ]
 
 [tool.hatch.envs.hatch-static-analysis]
-features = ["mem0-memory", "local-chromium-browser", "agent-core-browser", "agent-core-code-interpreter", "a2a-client", "diagram", "rss", "use-computer", "twelvelabs", "elasticsearch-memory", "mongodb-memory"]
+features = ["mem0-memory", "local-chromium-browser", "agent-core-browser", "agent-core-code-interpreter", "a2a-client", "diagram", "rss", "use-computer", "twelvelabs", "elasticsearch-memory", "mongodb-memory", "apify"]
 dependencies = [
     "strands-agents>=1.0.0",
     "mypy>=0.981,<1.0.0",
@@ -141,7 +144,7 @@ lint-check = [
 lint-fix = ["ruff check --fix"]
 
 [tool.hatch.envs.hatch-test]
-features = ["mem0-memory", "local-chromium-browser",  "agent-core-browser", "agent-core-code-interpreter", "a2a-client", "diagram", "rss", "use-computer", "twelvelabs", "elasticsearch-memory", "mongodb-memory"]
+features = ["mem0-memory", "local-chromium-browser",  "agent-core-browser", "agent-core-code-interpreter", "a2a-client", "diagram", "rss", "use-computer", "twelvelabs", "elasticsearch-memory", "mongodb-memory", "apify"]
 extra-dependencies = [
     "moto>=5.1.0,<6.0.0",
     "pytest>=8.0.0,<10.0.0",