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138 changes: 138 additions & 0 deletions apps/docs/content/docs/tools/arxiv.mdx
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---
title: ArXiv
description: Search and retrieve academic papers from ArXiv
---

import { BlockInfoCard } from "@/components/ui/block-info-card"

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type="arxiv"
color="#E0E0E0"
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{/* MANUAL-CONTENT-START:intro */}
[ArXiv](https://arxiv.org/) is a free, open-access repository of scientific research papers in fields such as physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, systems science, and economics. ArXiv provides a vast collection of preprints and published articles, making it a primary resource for researchers and practitioners worldwide.

With ArXiv, you can:

- **Search for academic papers**: Find research by keywords, author names, titles, categories, and more
- **Retrieve paper metadata**: Access abstracts, author lists, publication dates, and other bibliographic information
- **Download full-text PDFs**: Obtain the complete text of most papers for in-depth study
- **Explore author contributions**: View all papers by a specific author
- **Stay up-to-date**: Discover the latest submissions and trending topics in your field

In Sim Studio, the ArXiv integration enables your agents to programmatically search, retrieve, and analyze scientific papers from ArXiv. This allows you to automate literature reviews, build research assistants, or incorporate up-to-date scientific knowledge into your agentic workflows. Use ArXiv as a dynamic data source for research, discovery, and knowledge extraction within your Sim Studio projects.
{/* MANUAL-CONTENT-END */}


## Usage Instructions

Search for academic papers, retrieve metadata, download papers, and access the vast collection of scientific research on ArXiv.



## Tools

### `arxiv_search`

Search for academic papers on ArXiv by keywords, authors, titles, or other fields.

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `query` | string | Yes | The search query to execute |
| `searchField` | string | No | Field to search in: all, ti \(title\), au \(author\), abs \(abstract\), co \(comment\), jr \(journal\), cat \(category\), rn \(report number\) |
| `maxResults` | number | No | Maximum number of results to return \(default: 10, max: 2000\) |
| `sortBy` | string | No | Sort by: relevance, lastUpdatedDate, submittedDate \(default: relevance\) |
| `sortOrder` | string | No | Sort order: ascending, descending \(default: descending\) |

#### Output

| Parameter | Type |
| --------- | ---- |
| `query` | string |
| `papers` | string |
| `totalResults` | string |

### `arxiv_get_paper`

Get detailed information about a specific ArXiv paper by its ID.

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `paperId` | string | Yes | ArXiv paper ID \(e.g., |

#### Output

| Parameter | Type |
| --------- | ---- |
| `paper` | string |

### `arxiv_get_author_papers`

Search for papers by a specific author on ArXiv.

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `authorName` | string | Yes | Author name to search for |
| `maxResults` | number | No | Maximum number of results to return \(default: 10, max: 2000\) |

#### Output

| Parameter | Type |
| --------- | ---- |
| `authorPapers` | string |
| `authorName` | string |
| `totalResults` | string |



## Block Configuration

### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `operation` | string | Yes | Operation |



### Outputs

| Output | Type | Description |
| ------ | ---- | ----------- |
| `papers` | json | papers output from the block |
| `totalResults` | number | totalResults output from the block |
| `paper` | json | paper output from the block |
| `authorPapers` | json | authorPapers output from the block |


## Notes

- Category: `tools`
- Type: `arxiv`
8 changes: 5 additions & 3 deletions apps/docs/content/docs/tools/exa.mdx
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Expand Up @@ -26,7 +26,7 @@ import { BlockInfoCard } from "@/components/ui/block-info-card"
/>

{/* MANUAL-CONTENT-START:intro */}
[Exa](https://exa.ai/) is an AI-powered search engine designed specifically for developers and researchers that provides highly relevant and up-to-date information from across the web. It combines advanced semantic search capabilities with AI understanding to deliver more accurate and contextually relevant results than traditional search engines.
[Exa](https://exa.ai/) is an AI-powered search engine designed specifically for developers and researchers, providing highly relevant and up-to-date information from across the web. It combines advanced semantic search capabilities with AI understanding to deliver more accurate and contextually relevant results than traditional search engines.

With Exa, you can:

Expand All @@ -35,14 +35,16 @@ With Exa, you can:
- **Access up-to-date information**: Retrieve current information from across the web
- **Find similar content**: Discover related resources based on content similarity
- **Extract webpage contents**: Retrieve and process the full text of web pages
- **Answer questions with citations**: Ask questions and receive direct answers with supporting sources
- **Perform research tasks**: Automate multi-step research workflows to gather, synthesize, and summarize information

In Sim Studio, the Exa integration allows your agents to search the web for information, retrieve content from specific URLs, and find similar resources - all programmatically through API calls. This enables your agents to access real-time information from the internet, enhancing their ability to provide accurate, current, and relevant responses. The integration is particularly valuable for research tasks, information gathering, content discovery, and answering questions that require up-to-date information from across the web.
In Sim Studio, the Exa integration allows your agents to search the web for information, retrieve content from specific URLs, find similar resources, answer questions with citations, and conduct research tasks—all programmatically through API calls. This enables your agents to access real-time information from the internet, enhancing their ability to provide accurate, current, and relevant responses. The integration is particularly valuable for research tasks, information gathering, content discovery, and answering questions that require up-to-date information from across the web.
{/* MANUAL-CONTENT-END */}


## Usage Instructions

Search the web, retrieve content, find similar links, and answer questions using Exa
Search the web, retrieve content, find similar links, and answer questions using Exa's powerful AI search capabilities.



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10 changes: 9 additions & 1 deletion apps/docs/content/docs/tools/firecrawl.mdx
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Expand Up @@ -44,8 +44,16 @@ With Firecrawl in Sim Studio, you can:
- **Handle JavaScript-heavy sites**: Process content from modern web applications that rely on JavaScript
- **Filter content**: Focus on specific parts of a page using CSS selectors
- **Process at scale**: Handle high-volume scraping needs with a reliable API
- **Search the web**: Perform intelligent web searches and retrieve structured results
- **Crawl entire sites**: Crawl multiple pages from a website and aggregate their content

The Firecrawl integration allows your agents to access and process web content programmatically without leaving the Sim Studio environment. This enables scenarios like research, content aggregation, data extraction, and information analysis from across the web. Your agents can gather information from websites, extract structured data, and use that information to make decisions or generate insights - all without having to navigate the complexities of raw HTML parsing or browser automation. Simply configure the Firecrawl block with your API key, provide the target URL, and your agents can immediately begin working with web content in a clean, structured format.
In Sim Studio, the Firecrawl integration enables your agents to access and process web content programmatically as part of their workflows. Supported operations include:

- **Scrape**: Extract structured content (Markdown, HTML, metadata) from a single web page.
- **Search**: Search the web for information using Firecrawl's intelligent search capabilities.
- **Crawl**: Crawl multiple pages from a website, returning structured content and metadata for each page.

This allows your agents to gather information from websites, extract structured data, and use that information to make decisions or generate insights—all without having to navigate the complexities of raw HTML parsing or browser automation. Simply configure the Firecrawl block with your API key, select the operation (Scrape, Search, or Crawl), and provide the relevant parameters. Your agents can immediately begin working with web content in a clean, structured format.
{/* MANUAL-CONTENT-END */}


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2 changes: 1 addition & 1 deletion apps/docs/content/docs/tools/google_calendar.mdx
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Expand Up @@ -90,7 +90,7 @@ In Sim Studio, the Google Calendar integration enables your agents to programmat

## Usage Instructions

Integrate Google Calendar functionality to create, read, update, and list calendar events within your workflow. Automate scheduling, check availability, and manage events using OAuth authentication. Email invitations are sent asynchronously and delivery depends on recipients
Integrate Google Calendar functionality to create, read, update, and list calendar events within your workflow. Automate scheduling, check availability, and manage events using OAuth authentication. Email invitations are sent asynchronously and delivery depends on recipients' Google Calendar settings.



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2 changes: 1 addition & 1 deletion apps/docs/content/docs/tools/image_generator.mdx
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Expand Up @@ -46,7 +46,7 @@ In Sim Studio, the DALL-E integration enables your agents to generate images pro

## Usage Instructions

Create high-quality images using OpenAI
Create high-quality images using OpenAI's image generation models. Configure resolution, quality, style, and other parameters to get exactly the image you need.



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2 changes: 1 addition & 1 deletion apps/docs/content/docs/tools/jina.mdx
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Expand Up @@ -63,7 +63,7 @@ This integration is particularly valuable for building agents that need to gathe

## Usage Instructions

Transform web content into clean, readable text using Jina AI
Transform web content into clean, readable text using Jina AI's advanced extraction capabilities. Extract meaningful content from websites while preserving important information and optionally gathering links.



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2 changes: 2 additions & 0 deletions apps/docs/content/docs/tools/meta.json
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Expand Up @@ -2,6 +2,7 @@
"items": [
"index",
"airtable",
"arxiv",
"browser_use",
"clay",
"confluence",
Expand Down Expand Up @@ -53,6 +54,7 @@
"wealthbox",
"webhook",
"whatsapp",
"wikipedia",
"x",
"youtube"
]
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12 changes: 11 additions & 1 deletion apps/docs/content/docs/tools/notion.mdx
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Expand Up @@ -29,7 +29,17 @@ With Notion, you can:
- **Connect information**: Link between pages and databases to create a knowledge network
- **Access anywhere**: Use Notion across web, desktop, and mobile platforms with automatic syncing

In Sim Studio, the Notion integration enables your agents to interact directly with your Notion workspace programmatically. This allows for powerful automation scenarios such as knowledge management, content creation, and information retrieval. Your agents can read existing Notion pages to extract information, write to pages to update content, and create new pages from scratch. This integration bridges the gap between your AI workflows and your knowledge base, enabling seamless documentation and information management. By connecting Sim Studio with Notion, you can automate documentation processes, maintain up-to-date information repositories, generate reports, and organize information intelligently - all through your intelligent agents.
In Sim Studio, the Notion integration enables your agents to interact directly with your Notion workspace programmatically. This allows for powerful automation scenarios such as knowledge management, content creation, and information retrieval. Your agents can:

- **Read Notion pages**: Extract content and metadata from any Notion page.
- **Read Notion databases**: Retrieve database structure and information.
- **Write to pages**: Append new content to existing Notion pages.
- **Create new pages**: Generate new Notion pages under a parent page, with custom titles and content.
- **Query databases**: Search and filter database entries using advanced filter and sort criteria.
- **Search workspace**: Search across your entire Notion workspace for pages or databases matching specific queries.
- **Create new databases**: Programmatically create new databases with custom properties and structure.

This integration bridges the gap between your AI workflows and your knowledge base, enabling seamless documentation and information management. By connecting Sim Studio with Notion, you can automate documentation processes, maintain up-to-date information repositories, generate reports, and organize information intelligently—all through your intelligent agents.
{/* MANUAL-CONTENT-END */}


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2 changes: 1 addition & 1 deletion apps/docs/content/docs/tools/openai.mdx
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Expand Up @@ -43,7 +43,7 @@ In Sim Studio, the OpenAI integration enables your agents to leverage these powe

## Usage Instructions

Convert text into numerical vector representations using OpenAI
Convert text into numerical vector representations using OpenAI's embedding models. Transform text data into embeddings for semantic search, clustering, and other vector-based operations.



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2 changes: 1 addition & 1 deletion apps/docs/content/docs/tools/pinecone.mdx
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Expand Up @@ -45,7 +45,7 @@ In Sim Studio, the Pinecone integration enables your agents to leverage vector s

## Usage Instructions

Store, search, and retrieve vector embeddings using Pinecone
Store, search, and retrieve vector embeddings using Pinecone's specialized vector database. Generate embeddings from text and perform semantic similarity searches with customizable filtering options.



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21 changes: 21 additions & 0 deletions apps/docs/content/docs/tools/qdrant.mdx
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Expand Up @@ -80,6 +80,27 @@ import { BlockInfoCard } from "@/components/ui/block-info-card"
</svg>`}
/>

{/* MANUAL-CONTENT-START:intro */}
[Qdrant](https://qdrant.tech) is an open-source vector database designed for efficient storage, management, and retrieval of high-dimensional vector embeddings. Qdrant enables fast and scalable semantic search, making it ideal for AI applications that require similarity search, recommendation systems, and contextual information retrieval.

With Qdrant, you can:

- **Store vector embeddings**: Efficiently manage and persist high-dimensional vectors at scale
- **Perform semantic similarity search**: Find the most similar vectors to a query vector in real time
- **Filter and organize data**: Use advanced filtering to narrow down search results based on metadata or payload
- **Fetch specific points**: Retrieve vectors and their associated payloads by ID
- **Scale seamlessly**: Handle large collections and high-throughput workloads

In Sim Studio, the Qdrant integration enables your agents to interact with Qdrant programmatically as part of their workflows. Supported operations include:

- **Upsert**: Insert or update points (vectors and payloads) in a Qdrant collection
- **Search**: Perform similarity search to find vectors most similar to a given query vector, with optional filtering and result customization
- **Fetch**: Retrieve specific points from a collection by their IDs, with options to include payloads and vectors

This integration allows your agents to leverage powerful vector search and management capabilities, enabling advanced automation scenarios such as semantic search, recommendation, and contextual retrieval. By connecting Sim Studio with Qdrant, you can build agents that understand context, retrieve relevant information from large datasets, and deliver more intelligent and personalized responses—all without managing complex infrastructure.
{/* MANUAL-CONTENT-END */}


## Usage Instructions

Store, search, and retrieve vector embeddings using Qdrant. Perform semantic similarity searches and manage your vector collections.
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15 changes: 5 additions & 10 deletions apps/docs/content/docs/tools/reddit.mdx
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Expand Up @@ -26,19 +26,14 @@ import { BlockInfoCard } from "@/components/ui/block-info-card"
/>

{/* MANUAL-CONTENT-START:intro */}
[Reddit](https://www.reddit.com/) is a vast social news aggregation, content rating, and discussion platform where registered users submit content such as text posts, images, and links, which are then voted up or down by other members. Known as "the front page of the internet," Reddit is organized into thousands of communities called subreddits, each focused on a specific topic.
[Reddit](https://www.reddit.com/) is a social platform where users share and discuss content in topic-based communities called subreddits.

With Reddit, you can:
In Sim Studio, you can use the Reddit integration to:

- **Access diverse content**: Browse thousands of specialized communities covering virtually every topic
- **Stay informed**: Get real-time updates on trending news, discussions, and viral content
- **Engage with communities**: Participate in discussions with like-minded individuals
- **Discover trending topics**: See what's popular across different interest groups
- **Gather insights**: Collect opinions, feedback, and perspectives from diverse user groups
- **Monitor public sentiment**: Track reactions and discussions around specific topics or brands
- **Research niche topics**: Access specialized knowledge in dedicated communities
- **Get Posts**: Retrieve posts from any subreddit, with options to sort (Hot, New, Top, Rising) and filter Top posts by time (Day, Week, Month, Year, All Time).
- **Get Comments**: Fetch comments from a specific post, with options to sort and set the number of comments.

In Sim Studio, the Reddit integration enables your agents to programmatically access and analyze content from Reddit's vast ecosystem. This allows for powerful automation scenarios such as trend monitoring, content aggregation, and sentiment analysis. Your agents can retrieve popular posts from specific subreddits, extract valuable information, and incorporate these insights into their workflows. This integration bridges the gap between social media monitoring and your AI workflows, enabling more informed decision-making based on public discussions and trending topics. By connecting Sim Studio with Reddit, you can create agents that stay on top of relevant conversations, identify emerging trends, gather diverse perspectives, and deliver timely insights - all without requiring manual browsing of countless Reddit threads.
These operations let your agents access and analyze Reddit content as part of your automated workflows.
{/* MANUAL-CONTENT-END */}


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2 changes: 1 addition & 1 deletion apps/docs/content/docs/tools/serper.mdx
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Expand Up @@ -78,7 +78,7 @@ In Sim Studio, the Serper integration enables your agents to leverage the power

## Usage Instructions

Access real-time web search results with Serper
Access real-time web search results with Serper's Google Search API integration. Retrieve structured search data including web pages, news, images, and places with customizable language and region settings.



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