docs: fix links (#2206)

fix dead link to milvus
fix redirects

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> Standardizes and fixes documentation links across multiple pages to
remove redirects, point to current domains, and prefer internal docs
where available.
> 
> - Update external URLs (e.g., Cursor, Claude, Authy, Skyfire) and AWS
Bedrock docs to current paths
> - Switch various references to internal Apify docs (e.g., `Terms &
Conditions` to `/legal/store-publishing-terms-and-conditions`, `Apify
Actor Documentation` to `/platform/actors`, webhooks/actors links in
Windmill)
> - Refresh LangChain and LlamaIndex doc links to new
`docs.langchain.com` and `developers.llamaindex.ai` structures; align
JS/Python references
> - Normalize integration docs links for Kestra, Airbyte, n8n, and MCP
spec (`modelcontextprotocol.io/.../intro`)
> - Minor copy updates reflecting link changes (e.g., quick-start
`Cursor` URL)
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
10c4ead. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

Author: TC-MO

sources/platform/actors/development/quick-start/build_with_ai.md

@@ -21,7 +21,7 @@ This guide provides best practices for building new Actors or improving existing
 
 ## AI coding assistant instructions
 
-Use the following prompt in your AI coding assistant such as [Cursor](https://www.cursor.com/), [Claude Code](https://www.claude.com/product/claude-code) or [GitHub Copilot](https://github.com/features/copilot):
+Use the following prompt in your AI coding assistant such as [Cursor](https://cursor.com/), [Claude Code](https://claude.com/product/claude-code) or [GitHub Copilot](https://github.com/features/copilot):
 
 <PromptButton prompt={AGENTS_PROMPT} title="Use pre-built prompt for your AI coding assistant" />
 

sources/platform/actors/publishing/monetize/index.mdx

@@ -77,14 +77,14 @@ All other changes (such as decreasing prices, adjusting descriptions, or removin
 
 :::important Frequency of major monetization adjustments
 
-You can make major monetization changes to each Actor only **once per month**. After making a major change, you must wait until it takes effect (14 days) plus an additional period before making another major change. For further information & guidelines, please refer to our [Terms & Conditions](https://apify.com/store-terms-and-conditions)
+You can make major monetization changes to each Actor only **once per month**. After making a major change, you must wait until it takes effect (14 days) plus an additional period before making another major change. For further information & guidelines, please refer to our [Terms & Conditions](/legal/store-publishing-terms-and-conditions)
 
 :::
 
 ## Monthly payouts and analytics
 
 Payout invoices are automatically generated on the 11th of each month, summarizing the profits from all your Actors for the previous month.
-In accordance with our [Terms & Conditions](https://apify.com/store-terms-and-conditions), only funds from legitimate users who have already paid are included in the payout invoice.
+In accordance with our [Terms & Conditions](/legal/store-publishing-terms-and-conditions), only funds from legitimate users who have already paid are included in the payout invoice.
 
 :::note How negative profits are handled
 
@@ -98,7 +98,7 @@ If no action is taken, the payout will be automatically approved on the 14th, wi
 - $20 for PayPal
 - $100 for other payout methods
 
-If the monthly profit does not meet these thresholds, as per our [Terms & Conditions](https://apify.com/store-terms-and-conditions), the funds will roll over to the next month until the threshold is reached.
+If the monthly profit does not meet these thresholds, as per our [Terms & Conditions](/legal/store-publishing-terms-and-conditions), the funds will roll over to the next month until the threshold is reached.
 
 ## Handle free users
 

sources/platform/console/two-factor-authentication.md

@@ -26,7 +26,7 @@ If it's not enabled, click on the **Enable** button. You should see the two-fact
 
 ![Apify Console setup two-factor authentication - app](./images/console-two-factor-app-setup.png)
 
-In this view, you can use your favorite authenticator app to scan the QR code. We recommend using Google Authenticator ([Google Play Store](https://play.google.com/store/apps/details?id=com.google.android.apps.authenticator2&hl=en_US)/[Apple App Store](https://apps.apple.com/us/app/google-authenticator/id388497605)) or [Authy](https://authy.com/)([Google Play Store](https://play.google.com/store/apps/details?id=com.authy.authy)/[Apple App Store](https://apps.apple.com/us/app/twilio-authy/id494168017) but any other authenticator app should work as well.
+In this view, you can use your favorite authenticator app to scan the QR code. We recommend using Google Authenticator ([Google Play Store](https://play.google.com/store/apps/details?id=com.google.android.apps.authenticator2&hl=en_US)/[Apple App Store](https://apps.apple.com/us/app/google-authenticator/id388497605)) or [Authy](https://www.authy.com/)([Google Play Store](https://play.google.com/store/apps/details?id=com.authy.authy)/[Apple App Store](https://apps.apple.com/us/app/twilio-authy/id494168017) but any other authenticator app should work as well.
 
 You can also set up your app/browser extension manually without the QR code. To do that, click on the **Setup key** link below the QR code. This view with the key will pop up:
 

sources/platform/integrations/ai/agno.md

@@ -140,6 +140,6 @@ Agno supports any Apify Actor via the ApifyTools class. You can specify a single
 - [How to build an AI Agent](https://blog.apify.com/how-to-build-an-ai-agent/)
 - [Agno Framework Documentation](https://docs.agno.com)
 - [Apify Platform Documentation](https://docs.apify.com)
-- [Apify Actor Documentation](https://docs.apify.com/actors)
+- [Apify Actor Documentation](/platform/actors)
 - [Apify Store - Browse available Actors](https://apify.com/store)
 - [Agno Apify Toolkit Documentation](https://docs.agno.com/tools/toolkits/others/apify#apify)

sources/platform/integrations/ai/aws_bedrock.md

@@ -26,7 +26,7 @@ Before getting started, ensure you have:
 
 - An active AWS Account.
 - An Apify account and an [API token](https://docs.apify.com/platform/integrations/api#api-token).
-- Granted access to any Large Language Model from Amazon Bedrock. To add access to a LLM, follow this [guide](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html). We'll use **Anthropic Claude 3.5 Sonnet** in this example.
+- Granted access to any Large Language Model from Amazon Bedrock. To add access to a LLM, follow this [guide](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html). We'll use **Anthropic Claude 3.5 Sonnet** in this example.
 
 The overall process for creating an agent includes the following [steps](https://docs.aws.amazon.com/bedrock/latest/userguide/agents.html):
 

sources/platform/integrations/ai/langchain.md

@@ -10,13 +10,13 @@ slug: /integrations/langchain
 
 ---
 
-> For more information on LangChain visit its [documentation](https://python.langchain.com/docs/).
+> For more information on LangChain visit its [documentation](https://docs.langchain.com/oss/python/langchain/overview).
 
 In this example, we'll use the [Website Content Crawler](https://apify.com/apify/website-content-crawler) Actor, which can deeply crawl websites such as documentation, knowledge bases, help centers, or blogs and extract text content from the web pages.
 Then we feed the documents into a vector index and answer questions from it.
 
 This example demonstrates how to integrate Apify with LangChain using the Python language.
-If you prefer to use JavaScript, you can follow the  [JavaScript LangChain documentation](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/apify_dataset/).
+If you prefer to use JavaScript, you can follow the  [JavaScript LangChain documentation](https://docs.langchain.com/oss/javascript/integrations/document_loaders/web_loaders/apify_dataset).
 
 Before we start with the integration, we need to install all dependencies:
 
@@ -54,7 +54,7 @@ llm = ChatOpenAI(model="gpt-4o-mini")
 
 loader = apify.call_actor(
     actor_id="apify/website-content-crawler",
-    run_input={"startUrls": [{"url": "https://python.langchain.com/docs/get_started/introduction"}], "maxCrawlPages": 10, "crawlerType": "cheerio"},
+    run_input={"startUrls": [{"url": "https://docs.langchain.com/oss/python/langchain/quickstart"}], "maxCrawlPages": 10, "crawlerType": "cheerio"},
     dataset_mapping_function=lambda item: Document(
         page_content=item["text"] or "", metadata={"source": item["url"]}
     ),
@@ -107,7 +107,7 @@ llm = ChatOpenAI(model="gpt-4o-mini")
 print("Call website content crawler ...")
 loader = apify.call_actor(
     actor_id="apify/website-content-crawler",
-    run_input={"startUrls": [{"url": "https://python.langchain.com/docs/get_started/introduction"}], "maxCrawlPages": 10, "crawlerType": "cheerio"},
+    run_input={"startUrls": [{"url": "https://docs.langchain.com/oss/python/langchain/quickstart"}], "maxCrawlPages": 10, "crawlerType": "cheerio"},
     dataset_mapping_function=lambda item: Document(page_content=item["text"] or "", metadata={"source": item["url"]}),
 )
 print("Compute embeddings...")
@@ -130,7 +130,7 @@ After running the code, you should see the following output:
 answer: LangChain is a framework designed for developing applications powered by large language models (LLMs). It simplifies the
  entire application lifecycle, from development to productionization and deployment. LangChain provides open-source components and integrates with various third-party tools, making it easier to build and optimize applications using language models.
 
-source: https://python.langchain.com/docs/get_started/introduction
+source: https://docs.langchain.com/oss/python/langchain/quickstart
 ```
 
 LangChain is a standard interface through which you can interact with a variety of large language models (LLMs).
@@ -154,6 +154,6 @@ Similarly, you can use other Apify Actors to load data into LangChain and query
 
 ## Resources
 
-- [LangChain introduction](https://python.langchain.com/docs/get_started/introduction)
-- [Apify Dataset loader](https://python.langchain.com/docs/integrations/document_loaders/apify_dataset)
-- [LangChain Apify Provider](https://python.langchain.com/docs/integrations/providers/apify)
+- [LangChain quickstart](https://docs.langchain.com/oss/python/langchain/quickstart)
+- [Apify Dataset loader](https://docs.langchain.com/oss/python/integrations/document_loaders/apify_dataset)
+- [LangChain Apify Provider](https://docs.langchain.com/oss/python/integrations/providers/apify)

sources/platform/integrations/ai/langflow.md

@@ -12,7 +12,7 @@ slug: /integrations/langflow
 
 ## What is Langflow
 
-[Langflow](https://langflow.org/) is a low-code, visual tool that enables developers to build powerful AI agents and workflows that can use any API, models, or databases.
+[Langflow](https://www.langflow.org/) is a low-code, visual tool that enables developers to build powerful AI agents and workflows that can use any API, models, or databases.
 
 :::note Explore Langflow
 
@@ -37,7 +37,7 @@ This guide will demonstrate two different ways to use Apify Actors with Langflow
 
 :::note Cloud vs local setup
 
-Langflow can either be installed locally or used in the cloud. The cloud version is available on the [Langflow](http://langflow.org/) website. If you are using the cloud version, you can skip the installation step, and go straight to [Creating a new flow](#creating-a-new-flow)
+Langflow can either be installed locally or used in the cloud. The cloud version is available on the [Langflow](https://www.langflow.org/) website. If you are using the cloud version, you can skip the installation step, and go straight to [Creating a new flow](#creating-a-new-flow)
 
 :::
 

sources/platform/integrations/ai/llama.md

@@ -10,7 +10,7 @@ slug: /integrations/llama-index
 
 ---
 
-> For more information on LlamaIndex, visit its [documentation](https://docs.llamaindex.ai/en/stable/).
+> For more information on LlamaIndex, visit its [documentation](https://developers.llamaindex.ai/python/framework/).
 
 ## What is LlamaIndex?
 
@@ -76,4 +76,4 @@ documents = reader.load_data(
 ## Resources
 
 * [Apify loaders](https://llamahub.ai/l/readers/llama-index-readers-apify)
-* [LlamaIndex documentation](https://docs.llamaindex.ai/en/stable/)
+* [LlamaIndex documentation](https://developers.llamaindex.ai/python/framework/)

sources/platform/integrations/ai/mastra.md

@@ -31,7 +31,7 @@ This guide demonstrates how to integrate Apify Actors with Mastra by building an
 ### Prerequisites
 
 - _Apify API token_: To use Apify Actors, you need an Apify API token. Learn how to obtain it in the [Apify documentation](https://docs.apify.com/platform/integrations/api).
-- _LLM provider API key_: To power the agents, you need an LLM provider API key. For example, get one from the [OpenAI](https://platform.openai.com/account/api-keys) or [Anthropic](https://console.anthropic.com/settings/keys).
+- _LLM provider API key_: To power the agents, you need an LLM provider API key. For example, get one from the [OpenAI](https://platform.openai.com/account/api-keys) or [Anthropic](https://platform.claude.com/settings/keys).
 - _Node.js_: Ensure you have Node.js installed.
 - _Packages_: Install the following packages:
 

sources/platform/integrations/ai/mcp.md

@@ -13,7 +13,7 @@ import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 
 The Apify's MCP server ([mcp.apify.com](https://mcp.apify.com)) allows AI applications and agents to interact with the Apify platform
-using [Model Context Protocol](https://modelcontextprotocol.io/). The server enables AI agents to
+using [Model Context Protocol](https://modelcontextprotocol.io/docs/getting-started/intro). The server enables AI agents to
 discover and run Actors from [Apify Store](https://apify.com/store), access storages and results,
 and enabled AI coding assistants to access Apify documentation and tutorials.