# Documentation Collection

> Combined documentation from multiple sources

## Main Website

- [About Parallel | The web's second user | Parallel Web Systems | Build the world wide web for AIs](/about.md) (1093 tokens): The web's second user. Building web search and infrastructure for AIs.
- [Parallel Web Systems | Build the world wide web for AIs](/articles.md) (325 tokens): Parallel builds web data and APIs for AI agents—turning web search and knowledge tasks into programmable, enterprise-ready infrastructure.
- [AI Web Search and AI Deep Research for Sales Enrichment  | Parallel Web Systems | Build the world wide web for AIs](/articles/ai-web-enrichment-for-sales.md) (3469 tokens): Deep research AI sales web enrichment using AI search APIs. Create custom prospect intelligence beyond Apollo/ZoomInfo with automated data gathering tools.
- [What is a web crawler and how does it work? Full guide. | Parallel Web Systems | Build the world wide web for AIs](/articles/what-is-a-web-crawler.md) (3618 tokens): Parallel builds web data and APIs for AI agents—turning web search and knowledge tasks into programmable, enterprise-ready infrastructure.
- [Parallel Web Systems | Build the world wide web for AIs](/articles/what-is-a-web-index.md) (3487 tokens): This document details the basics of web indexes and the benefits of building applications that can access them programmatically.
- [A comprehensive introduction to web search APIs and how they work | Parallel Web Systems | Build the world wide web for AIs](/articles/what-is-a-web-search-api.md) (3155 tokens): Web search APIs transform how AI systems access the web. This article explains search APIs and how they work to power a variety of enterprise AI use cases.
- [How web scraping works and is used by businesses in data pipelines | Parallel Web Systems | Build the world wide web for AIs](/articles/what-is-web-scraping.md) (3840 tokens): Web scraping is a technique used by businesses to gather data from public websites. This article explains web scraping and their applications in business.
- [Blog - Enterprise Deep Research API Insights | Parallel | Parallel Web Systems | Build the world wide web for AIs](/blog.md) (3661 tokens): Learn about enterprise deep research APIs, structured data extraction, and AI agent integration. Technical insights on building state-of-the-art web search for ChatGPT and Claude.
- [Case Study for Day AI using Parallel Task API | Parallel Web Systems | Build the world wide web for AIs](/blog/case-study-day-ai.md) (1474 tokens): With Parallel’s web search technology backing it, Day provides superior visibility of insights across private and public data.
- [Gumloop and Parallel Search API Case Study | Parallel Web Systems | Build the world wide web for AIs](/blog/case-study-gumloop.md) (1545 tokens): By integrating Parallel's Task API as a core component, Gumloop enables businesses to build AI automation workflows that are grounded in real-time web data.
- [Introducing the Parallel Chat API | Parallel Web Systems | Build the world wide web for AIs](/blog/chat-api.md) (1087 tokens): Introducing the Parallel Chat API, a state-of-the-art low latency AI web research and search API for web-based LLM completions that deliver real-time deep research capabilities through our rapidly growing web index. The Parallel Chat API returns OpenAI ChatCompletions compatible streaming responses in both text and structured JSON format, enabling seamless OpenAI search integration for interactive applications requiring instant web automation tools and web research capabilities. Built with the same price-performance obsession as the Parallel Task API, the Parallel Chat API functions as an advanced AI web search alternative that transforms any application into a powerful web research platform.
- [Building a Serverless Competitive Intelligence Platform with MCP + Task API | Parallel Web Systems | Build the world wide web for AIs](/blog/cookbook-competitor-research-with-reddit-mcp.md) (6402 tokens): Build a competitive intelligence platform with the Parallel Task API configured with Reddit MCP tool calls.
- [Building a Full-Stack Search Agent with Parallel and Cerebras | Parallel Web Systems | Build the world wide web for AIs](/blog/cookbook-search-agent.md) (4737 tokens): Build a web research agent that combines Parallel's Search API with streaming AI inference.
- [Building a real-time streaming task manager with Parallel | Parallel Web Systems | Build the world wide web for AIs](/blog/cookbook-sse-task-manager-with-parallel.md) (4238 tokens): This cookbook details how to build a task streaming playground that showcases Parallel's Task API with real-time Server-Sent Events (SSE).
- [Parallel AI releases new Core2x processor for Task API | Parallel Web Systems | Build the world wide web for AIs](/blog/core2x-processor.md) (907 tokens): The new Core2x processor now is available in the Parallel Task API to offer developers finer control.
- [A new pareto-frontier for Deep Research price-performance | Parallel Web Systems | Build the world wide web for AIs](/blog/deep-research-benchmarks.md) (3132 tokens): Expanded results that demonstrate Parallel's complete price-performance advantage in Deep Research.
- [Parallel Deep Research Reports | Parallel Web Systems | Build the world wide web for AIs](/blog/deep-research-reports.md) (1100 tokens): The Parallel Task API now supports comprehensive markdown Deep Research report generation with in-line citations and relevant excerpts.
- [State of the Art Deep Research APIs | Parallel Web Systems | Build the world wide web for AIs](/blog/deep-research.md) (1993 tokens): Parallel Task API processors achieve state-of-the-art 27% accuracy on the BrowseComp benchmark—beating every other commercial API.
- [The full Basis framework is now available in Base and Lite processors | Parallel Web Systems | Build the world wide web for AIs](/blog/full-basis-framework-for-task-api.md) (2271 tokens): Lite and Base Task API processors now include the complete Basis framework—citations, reasoning, excerpts, and calibrated confidence scores.
- [Introducing Basis with Calibrated Confidences  | Parallel Web Systems | Build the world wide web for AIs](/blog/introducing-basis-with-calibrated-confidences.md) (2537 tokens): Parallel Web Systems introduces Basis with calibrated confidences - a new verification framework for AI web research and search API outputs that sets a new industry standard for transparent and reliable deep research. Basis provides comprehensive citations, detailed reasoning, confidence scoring, and source evidence for every Task API response, enabling enterprises to identify when AI web research may yield unreliable results and implement targeted human-in-the-loop workflows. Through rigorous calibration testing, Basis confidences serve as accurate proxies for performance evaluation, with high-confidence outputs achieving 2-3x lower error rates than overall datasets.
- [Introducing Parallel | Web Search Infrastructure for AIs  | Parallel Web Systems | Build the world wide web for AIs](/blog/introducing-parallel.md) (3037 tokens): The Parallel Deep Research API outperforms humans and all leading AI models
- [Introducing Tool Calling via MCP Servers | Parallel Web Systems | Build the world wide web for AIs](/blog/mcp-tool-calling.md) (899 tokens): Starting today, the Parallel Task API supports Tool Calling via MCP Servers in beta. With a single API call, you can now bring your own tools, data sources, and execution logic directly into web research workflows.
- [A new line of advanced processors: Ultra2x, Ultra4x, and Ultra8x  | Parallel Web Systems | Build the world wide web for AIs](/blog/new-advanced-processors.md) (863 tokens): New advanced processors are now available with the Parallel Task API, giving you granular control over compute allocation for critical research workflows. Last month, we demonstrated that accuracy scales consistently with compute budget on BrowseComp, achieving 39% and 48% accuracy with 2x and 4x compute respectively. These processors are now available as Ultra2x and Ultra4x, alongside our most advanced processor yet—Ultra8x.
- [Introducing the Parallel Search API  | Parallel Web Systems | Build the world wide web for AIs](/blog/parallel-search-api.md) (1112 tokens): The Parallel Search API is a new AI search engine API that transforms web search for Large Language Models and AI agents. Built on Parallel's custom web crawler and index, the Search API takes flexible inputs (search objective and/or search queries) and returns LLM-ready ranked URLs with extended webpage excerpts. Unlike traditional search APIs designed for human use, this AI-native search API delivers high-density, information-rich content optimized for direct LLM consumption, eliminating complex multi-step pipelines of searching, scraping, and parsing.
- [Parallel Search MCP Server in Devin | Parallel Web Systems | Build the world wide web for AIs](/blog/parallel-search-mcp-in-devin.md) (833 tokens): The Parallel Search MCP Server is now live in Devin's MCP Marketplace, bringing high quality web research capabilities directly to the AI software engineer. Devin can now query the web with the same infrastructure that powers our state-of-the-art Task and Chat APIs.
- [Introducing the Parallel Task API: The state-of-the-art API for automated AI deep web research | Parallel Web Systems | Build the world wide web for AIs](/blog/parallel-task-api.md) (2922 tokens): The Parallel Task API is a state-of-the-art system for automated web research that delivers the highest accuracy at every price point.
- [Introducing the Parallel Task MCP Server to help you research better | Parallel Web Systems | Build the world wide web for AIs](/blog/parallel-task-mcp-server.md) (1809 tokens): The Parallel Task MCP Server enables users to continue working in their MCP client while Parallel’s web search tasks run in the background.
- [A state-of-the-art search API purpose-built for agents | Parallel Web Systems | Build the world wide web for AIs](/blog/search-api-benchmark.md) (2032 tokens): The Parallel Search MCP Server offers an easy to integrate, state-of-the-art, web search solution for AI agents. Built on the same search infrastructure that powers Parallel’s Task API and Search API, it demonstrates superior performance while being up to 50% cheaper than LLM native web search implementations - establishing a new price-performance frontier for AI agent web access.
- [Introducing the Parallel Search MCP Server | Parallel Web Systems | Build the world wide web for AIs](/blog/search-mcp-server.md) (1080 tokens): The Parallel Search MCP Server exposes the Parallel Search API as a plug-and-play tool, giving LLMs instant access to real-time web knowledge with a simple configuration change. This replaces brittle, multi-step search stacks with a single, production-ready tool that delivers higher quality results at significantly lower cost.
- [Introducing Source Policy: Precise control over web research sources | Parallel Web Systems | Build the world wide web for AIs](/blog/source-policy.md) (893 tokens): Starting today, Source Policy is available for both the Parallel Task API and Search API - giving you granular control over which sources your AI agents access and how results are prioritized.
- [Parallel Web Systems | Build the world wide web for AIs](/blog/sse-for-tasks.md) (1946 tokens): Parallel builds web data and APIs for AI agents—turning web search and knowledge tasks into programmable, enterprise-ready infrastructure.
- [Introducing Auto Mode for the Parallel Task API | Parallel Web Systems | Build the world wide web for AIs](/blog/task-api-auto-mode.md) (865 tokens): Starting today, the Parallel Task API supports Auto Mode - enabling one-off web research queries without requiring explicit output schemas. Simply ask a research question and let our processors handle the rest.
- [Introducing the Parallel Task Group API  | Parallel Web Systems | Build the world wide web for AIs](/blog/task-group-api.md) (1092 tokens): Parallel launches Task Group API for batch web research at scale. Execute thousands of AI-powered data collection tasks with unified monitoring, real-time streaming, and intelligent failure handling. Now in public beta.
- [Introducing the Typescript SDK | Parallel Web Systems | Build the world wide web for AIs](/blog/typescript-sdk.md) (325 tokens): The Parallel TypeScript SDK is generally available - bringing strongly typed interfaces to all Parallel APIs.
- [Webhooks | Get notified when web research complete | Parallel Web Systems | Build the world wide web for AIs](/blog/webhooks.md) (1040 tokens): Parallel builds web data and APIs for AI agents—turning web search and knowledge tasks into programmable, enterprise-ready infrastructure.
- [Customer Terms  | Parallel Web Systems | Build the world wide web for AIs](/customer-terms.md) (8531 tokens): Customer Terms  - Parallel
- [Parallel Web Systems | Build the world wide web for AIs](/index.html.md) (2906 tokens): Parallel builds web data and APIs for AI agents—turning web search and knowledge tasks into programmable, enterprise-ready infrastructure.
- [Privacy Policy | Parallel Web Systems | Build the world wide web for AIs](/privacy-policy.md) (3395 tokens): Privacy Policy - Parallel
- [Deep Research API for ChatGPT & AI Agents | State-of-the-Art Performance | Parallel | Parallel Web Systems | Build the world wide web for AIs](/products/api.md) (574 tokens): Enterprise deep research API for AI agents. Up to 48% accuracy outperforms GPT-4 browsing (1%), Claude (6%), Perplexity (8%). LLM-native deep research with structured data extraction, MCP server integration, and SOC-II certified infrastructure. Built for complex multi-hop research workflows.
- [/products/find-all](/products/find-all.md) (0 tokens)
- [Terms | Parallel Web Systems | Build the world wide web for AIs](/terms-of-service.md) (2515 tokens): Terms - Parallel

## Docs

- [Search - Parallel](docs/api-reference/search-api/search.md) (1781 tokens): Searches the web.
- [Add Runs to Task Group - Parallel](docs/api-reference/task-api-beta/add-runs-to-task-group.md) (4107 tokens): Initiates multiple task runs within a TaskGroup.
- [Create Task Group - Parallel](docs/api-reference/task-api-beta/create-task-group.md) (1349 tokens): Initiates a TaskGroup to group and track multiple runs.
- [Fetch Task Group Runs - Parallel](docs/api-reference/task-api-beta/fetch-task-group-runs.md) (5684 tokens): Retrieves task runs in a TaskGroup and optionally their inputs and outputs.

All runs within a TaskGroup are returned as a stream. To get the inputs and/or
outputs back in the stream, set the corresponding `include_input` and
`include_output` parameters to `true`.

The stream is resumable using the `event_id` as the cursor. To resume a stream,
specify the `last_event_id` parameter with the `event_id` of the last event in the
stream. The stream will resume from the next event after the `last_event_id`.
- [Retrieve Task Group Run - Parallel](docs/api-reference/task-api-beta/retrieve-task-group-run.md) (2060 tokens): Retrieves run status by run_id.

This endpiont is equivalent to fetching run status directly using the
`retrieve()` method or the `tasks/runs` GET endpoint.

The run result is available from the `/result` endpoint.
- [Retrieve Task Group - Parallel](docs/api-reference/task-api-beta/retrieve-task-group.md) (1195 tokens): Retrieves aggregated status across runs in a TaskGroup.
- [Stream Task Group Events - Parallel](docs/api-reference/task-api-beta/stream-task-group-events.md) (5926 tokens): Streams events from a TaskGroup: status updates and run completions.

The connection will remain open for up to an hour as long as at least one run in the
group is still active.
- [Create Task Run - Parallel](docs/api-reference/task-api-v1/create-task-run.md) (5099 tokens): Initiates a task run.

Returns immediately with a run object in status 'queued'.

Beta features can be enabled by setting the 'parallel-beta' header.
- [Retrieve Task Run Input - Parallel](docs/api-reference/task-api-v1/retrieve-task-run-input.md) (2350 tokens): Retrieves the input of a run by run_id.
- [Retrieve Task Run Result - Parallel](docs/api-reference/task-api-v1/retrieve-task-run-result.md) (4627 tokens): Retrieves a run result by run_id, blocking until the run is completed.
- [Retrieve Task Run - Parallel](docs/api-reference/task-api-v1/retrieve-task-run.md) (1998 tokens): Retrieves run status by run_id.

The run result is available from the `/result` endpoint.
- [Stream Task Run Events - Parallel](docs/api-reference/task-api-v1/stream-task-run-events.md) (6099 tokens): Streams events for a task run.

Returns a stream of events showing progress updates and state changes for the task
run.

For task runs that did not have enable_events set to true during creation, the
frequency of events will be reduced.
- [Quickstart - Parallel](docs/chat-api/chat-quickstart.md) (2523 tokens): Get started with the Parallel Chat API
- [OpenAI SDK Compatibility - Parallel](docs/chat-api/sdk-compatibility.md) (1011 tokens): OpenAI SDK compatibility features and limitations
- [Quickstart - Parallel](docs/findall-api/findall-quickstart.md) (1669 tokens): Get Started with the Parallel FindAll API
- [Choose a Processor - Parallel](docs/findall-api/guides/choose-a-processor.md) (319 tokens): FindAll API pricing structure and processors
- [Reference Endpoints - Parallel](docs/findall-api/guides/reference-endpoints.md) (2034 tokens): API Reference for the Alpha API
- [Understand Data Models - Parallel](docs/findall-api/guides/understand-data-models.md) (437 tokens): Descriptions and examples for each of the Find All API Data Models
- [Parallel Documentation - Parallel](docs/home.md) (4322 tokens): Explore Parallel's web API products for building intelligent applications.
- [AWS Marketplace - Parallel](docs/integrations/aws-marketplace.md) (684 tokens): Access Parallel's API through the AWS Marketplace
- [Getting started - Parallel](docs/integrations/mcp/getting-started.md) (1294 tokens): Get started using Parallel MCPs
- [Programmatic Use - Parallel](docs/integrations/mcp/programmatic-use.md) (2167 tokens): How to use the MCP servers Programmatically
- [Task MCP - Parallel](docs/integrations/mcp/task-mcp.md) (1378 tokens): Learn about the Task MCP and how to use it
- [n8n - Parallel](docs/integrations/n8n.md) (489 tokens): Use Parallel in n8n Automations
- [OAuth Provider - Parallel](docs/integrations/oauth-provider.md) (857 tokens): Integrate with the Parallel OAuth Provider to get a Parallel API key on behalf of your users
- [Changelog - Parallel](docs/resources/changelog.md) (7685 tokens): Product updates from the Parallel team
- [Crawler - Parallel](docs/resources/crawler.md) (192 tokens): This documentation provides guidance for webmasters on managing their website's interaction with our crawling system
- [FAQs - Parallel](docs/resources/faqs.md) (887 tokens): Common questions about the Task API
- [Rate Limits - Parallel](docs/resources/rate-limits.md) (97 tokens): Default rate limits
- [Source Policy - Parallel](docs/resources/source-policy.md) (540 tokens): Configure which domains are included or excluded from your web research results.
- [Warnings and Errors - Parallel](docs/resources/warnings-and-errors.md) (1040 tokens): Breakdown of warnings and errors
- [Processors - Parallel](docs/search-api/processors.md) (244 tokens): Choosing the right Processor for your use case
- [Quickstart - Parallel](docs/search-api/search-quickstart.md) (1940 tokens): Get started with the Parallel Search API
- [Task Group - Parallel](docs/task-api/group-api.md) (4456 tokens): Batch process Tasks at scale with the Parallel Task Group API
- [Access Research Basis - Parallel](docs/task-api/guides/access-research-basis.md) (1917 tokens): Understand how to access citations, reasoning, and confidence levels for your Task Run outputs
- [Choose a Processor - Parallel](docs/task-api/guides/choose-a-processor.md) (1351 tokens)
- [Execute Task Runs - Parallel](docs/task-api/guides/execute-task-run.md) (631 tokens): Understanding how Tasks Runs are created, processed, and returned
- [Specify a Task - Parallel](docs/task-api/guides/specify-a-task.md) (2602 tokens): Define structured research tasks with customizable input and output schemas.
- [Ingest API - Parallel](docs/task-api/ingest-api.md) (5127 tokens): API reference for creating awesome tasks
- [MCP Tool Calling - Parallel](docs/task-api/mcp-tool-call.md) (1413 tokens): Using MCP servers for tool calls in the Parallel Task API
- [Deep Research - Parallel](docs/task-api/task-deep-research.md) (2944 tokens): Natural language to structured intelligence with auto schema
- [Quickstart - Parallel](docs/task-api/task-quickstart.md) (4802 tokens): Start building web-based enrichment flows with the Parallel Task API
- [Streaming Events - Parallel](docs/task-api/task-sse.md) (1737 tokens): SSE for Task Runs
- [Webhooks - Parallel](docs/task-api/webhooks.md) (1782 tokens): Webhook events for task run completions

## SDKs

- [Python SDK Footprint](custom/python-sdk.md) (2861 tokens): All API info needed to use the Python SDK. Does not include all APIs
- [Typescript SDK Footprint](custom/typescript-sdk.md) (8015 tokens): All API info needed to use the Typescript SDK. Does not include all APIs