Parallel.ai
132 lines. Parallel.ai came to play.
Dive into the world of Parallel.ai, where cutting-edge AI tools transform how businesses interact with data. Their llms.txt showcases innovative features like chat completions and content extraction, making complex tasks a breeze. Get ready to elevate your operations!
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Parallel.ai's llms.txt Insights
Short and sweet
3 sections. Minimalist, but hey — at least they showed up.
Goldilocks zone
132 lines — not too long, not too short. AI loves this.
Double trouble
Runs both llms.txt and llms-full.txt. Someone takes this seriously.
What's inside Parallel.ai's llms.txt
Parallel.ai's llms.txt contains 2 sections:
- Parallel
- Docs
How does Parallel.ai's llms.txt compare?
| Parallel.ai | Directory Avg | Top Performer | |
|---|---|---|---|
| Lines | 132 | 1029 | 163,447 |
| Sections | 3 | 17 | 3207 |
Cool table. Now the real question — where do you land? Find out →
Parallel.ai's llms.txt preview
First 100 of 132 lines
# Parallel
## Docs
- [Chat Completions](https://docs.parallel.ai/api-reference/chat-api-beta/chat-completions.md): Chat completions.
- [Extract](https://docs.parallel.ai/api-reference/extract-beta/extract.md): Extracts relevant content from specific web URLs.
- [Add Enrichment to FindAll Run](https://docs.parallel.ai/api-reference/findall-api-beta/add-enrichment-to-findall-run.md): Add an enrichment to a FindAll run.
- [Cancel FindAll Run](https://docs.parallel.ai/api-reference/findall-api-beta/cancel-findall-run.md): Cancel a FindAll run.
- [Create FindAll Run](https://docs.parallel.ai/api-reference/findall-api-beta/create-findall-run.md): Starts a FindAll run.
- [Extend FindAll Run](https://docs.parallel.ai/api-reference/findall-api-beta/extend-findall-run.md): Extend a FindAll run by adding additional matches to the current match limit.
- [FindAll Run Result](https://docs.parallel.ai/api-reference/findall-api-beta/findall-run-result.md): Retrieve the FindAll run result at the time of the request.
- [Get FindAll Run Schema](https://docs.parallel.ai/api-reference/findall-api-beta/get-findall-run-schema.md)
- [Ingest FindAll Run](https://docs.parallel.ai/api-reference/findall-api-beta/ingest-findall-run.md): Transforms a natural language search objective into a structured FindAll spec.
- [Retrieve FindAll Run Status](https://docs.parallel.ai/api-reference/findall-api-beta/retrieve-findall-run-status.md): Retrieve a FindAll run.
- [Stream FindAll Events](https://docs.parallel.ai/api-reference/findall-api-beta/stream-findall-events.md): Stream events from a FindAll run.
- [Create Monitor](https://docs.parallel.ai/api-reference/monitor/create-monitor.md): Create a web monitor.
- [Delete Monitor](https://docs.parallel.ai/api-reference/monitor/delete-monitor.md): Delete a monitor.
- [List Events](https://docs.parallel.ai/api-reference/monitor/list-events.md): List events for a monitor from up to the last 300 event groups.
- [List Monitors](https://docs.parallel.ai/api-reference/monitor/list-monitors.md): List active monitors.
- [List Monitors](https://docs.parallel.ai/api-reference/monitor/list-monitors-1.md): List active monitors ordered by creation time, newest first.
- [Retrieve Event Group](https://docs.parallel.ai/api-reference/monitor/retrieve-event-group.md): Retrieve an event group for a monitor.
- [Retrieve Monitor](https://docs.parallel.ai/api-reference/monitor/retrieve-monitor.md): Retrieve a monitor.
- [Simulate Event](https://docs.parallel.ai/api-reference/monitor/simulate-event.md): Simulate sending an event for a monitor.
- [Update Monitor](https://docs.parallel.ai/api-reference/monitor/update-monitor.md): Update a monitor.
- [Search](https://docs.parallel.ai/api-reference/search-beta/search.md): Searches the web.
- [Add Runs to Task Group](https://docs.parallel.ai/api-reference/tasks-beta/add-runs-to-task-group.md): Initiates multiple task runs within a TaskGroup.
- [Create Task Group](https://docs.parallel.ai/api-reference/tasks-beta/create-task-group.md): Initiates a TaskGroup to group and track multiple runs.
- [Fetch Task Group Runs](https://docs.parallel.ai/api-reference/tasks-beta/fetch-task-group-runs.md): Retrieves task runs in a TaskGroup and optionally their inputs and outputs.
- [Retrieve Task Group](https://docs.parallel.ai/api-reference/tasks-beta/retrieve-task-group.md): Retrieves aggregated status across runs in a TaskGroup.
- [Retrieve Task Group Run](https://docs.parallel.ai/api-reference/tasks-beta/retrieve-task-group-run.md): Retrieves run status by run_id.
- [Stream Task Group Events](https://docs.parallel.ai/api-reference/tasks-beta/stream-task-group-events.md): Streams events from a TaskGroup: status updates and run completions.
- [Create Task Run](https://docs.parallel.ai/api-reference/tasks-v1/create-task-run.md): Initiates a task run.
- [Retrieve Task Run](https://docs.parallel.ai/api-reference/tasks-v1/retrieve-task-run.md): Retrieves run status by run_id.
- [Retrieve Task Run Input](https://docs.parallel.ai/api-reference/tasks-v1/retrieve-task-run-input.md): Retrieves the input of a run by run_id.
- [Retrieve Task Run Result](https://docs.parallel.ai/api-reference/tasks-v1/retrieve-task-run-result.md): Retrieves a run result by run_id, blocking until the run is completed.
- [Stream Task Run Events](https://docs.parallel.ai/api-reference/tasks-v1/stream-task-run-events.md): Streams events for a task run.
- [OpenAI ChatCompletions Compatibility](https://docs.parallel.ai/chat-api/chat-quickstart.md): Build low-latency web research applications with OpenAI-compatible streaming chat completions
- [Google BigQuery](https://docs.parallel.ai/data-integrations/bigquery.md): Enrich data at scale using Parallel's SQL-native remote functions for BigQuery
- [DuckDB](https://docs.parallel.ai/data-integrations/duckdb.md): Enrich data at scale using Parallel's native DuckDB integration with batch processing
- [Data Integrations](https://docs.parallel.ai/data-integrations/overview.md): Enrich your data with web intelligence directly in your favorite data tools
- [Polars](https://docs.parallel.ai/data-integrations/polars.md): Enrich data at scale using Parallel's native Polars integration for DataFrames
- [Snowflake](https://docs.parallel.ai/data-integrations/snowflake.md): Enrich data at scale using Parallel's SQL-native UDTF for Snowflake
- [Apache Spark](https://docs.parallel.ai/data-integrations/spark.md): Enrich data at scale using Parallel's SQL-native UDFs for Apache Spark
- [Supabase](https://docs.parallel.ai/data-integrations/supabase.md): Enrich your Supabase data with live web intelligence using Edge Functions and Parallel
- [Extract API Best Practices](https://docs.parallel.ai/extract/best-practices.md): Learn how to optimize web content extraction with objectives, search queries, and fetch policies for LLM-ready markdown output
- [Extract API Quickstart](https://docs.parallel.ai/extract/extract-quickstart.md): Convert any public URL into clean, LLM-optimized markdown with the Parallel Extract API
- [Candidates](https://docs.parallel.ai/findall-api/core-concepts/findall-candidates.md): Understanding FindAll candidates, their structure, states, and how to exclude specific entities
- [Generators](https://docs.parallel.ai/findall-api/core-concepts/findall-generator-pricing.md): Choose the right FindAll generator (preview, base, core, pro) based on query complexity and expected match volume
- [Run Lifecycle](https://docs.parallel.ai/findall-api/core-concepts/findall-lifecycle.md): Understand FindAll run statuses, termination reasons, and how to cancel runs
- [Cancel](https://docs.parallel.ai/findall-api/features/findall-cancel.md): Stop FindAll runs early to control costs
- [Enrichments](https://docs.parallel.ai/findall-api/features/findall-enrich.md): Add non-boolean enrichment data to FindAll candidates without affecting match conditions
- [Extend](https://docs.parallel.ai/findall-api/features/findall-extend.md): Increase the match limit of existing FindAll runs to get more results without changing query criteria
- [Preview](https://docs.parallel.ai/findall-api/features/findall-preview.md): Test FindAll queries with a small sample of candidates before committing to full runs
- [Refresh Runs](https://docs.parallel.ai/findall-api/features/findall-refresh.md): Rerun the same FindAll query with exclude_list to discover net new entities over time
- [Streaming Events](https://docs.parallel.ai/findall-api/features/findall-sse.md): Receive real-time updates on FindAll runs using Server-Sent Events (SSE)
- [Webhooks](https://docs.parallel.ai/findall-api/features/findall-webhook.md): Receive real-time notifications on FindAll runs and candidates using webhooks
- [FindAll Migration Guide](https://docs.parallel.ai/findall-api/findall-migration-guide.md): Guide for migrating from V0 to V1 FindAll API
- [FindAll API Quickstart](https://docs.parallel.ai/findall-api/findall-quickstart.md): Discover and enrich entities from the web using natural language queries with the FindAll API
- [Glossary](https://docs.parallel.ai/getting-started/glossary.md): Key terms and concepts used throughout Parallel's documentation
- [Overview](https://docs.parallel.ai/getting-started/overview.md): A high-level introduction to Parallel's APIs for web research, data enrichment, and intelligent automation
- [Pricing](https://docs.parallel.ai/getting-started/pricing.md)
- [Rate limits](https://docs.parallel.ai/getting-started/rate-limits.md): Default API rate limits for Search, Extract, Tasks, Chat, FindAll, and Monitor endpoints
- [Parallel Documentation](https://docs.parallel.ai/home.md): Explore Parallel's web API products for building intelligent applications.
- [Agent Skills](https://docs.parallel.ai/integrations/agent-skills.md): Add Parallel web search, extraction, deep research, and data enrichment to any AI coding agent
- [AWS Marketplace](https://docs.parallel.ai/integrations/aws-marketplace.md): Access Parallel's API through the AWS Marketplace
- [Browser Use](https://docs.parallel.ai/integrations/browseruse.md): Access private web data in Tasks using Browser Use MCP
- [Claude Code Plugin](https://docs.parallel.ai/integrations/claude-code-marketplace.md): Add Parallel web search, extraction, deep research, and data enrichment to Claude Code
- [ClawHub](https://docs.parallel.ai/integrations/clawhub.md): Install Parallel skills for OpenClaw from ClawHub — the skill registry for AI agents
- [Parallel CLI](https://docs.parallel.ai/integrations/cli.md): Command-line tool for web search, content extraction, data enrichment, deep research, entity discovery, and web monitoring
- [Cursor Plugin](https://docs.parallel.ai/integrations/cursor-marketplace.md): Add Parallel web search, extraction, deep research, and data enrichment to Cursor
- [Developer Tools Overview](https://docs.parallel.ai/integrations/developer-quickstart.md): Choose the right way to integrate Parallel into your AI workflow — CLI, MCP, or SDK
- [Google Vertex AI](https://docs.parallel.ai/integrations/google-vertex.md): Use Parallel with Google Vertex AI
- [Google Sheets](https://docs.parallel.ai/integrations/gsuite.md): Use Parallel directly in Google Sheets with the PARALLEL_QUERY function
- [LangChain](https://docs.parallel.ai/integrations/langchain.md): LangChain integrations for Parallel, enabling real-time web research and AI capabilities
- [Programmatic Use](https://docs.parallel.ai/integrations/mcp/programmatic-use.md): How to use the MCP servers Programmatically
- [Quickstart](https://docs.parallel.ai/integrations/mcp/quickstart.md): Install and configure Parallel MCP servers for AI assistants like Cursor, VS Code, and Claude Desktop
- [Search MCP](https://docs.parallel.ai/integrations/mcp/search-mcp.md): Add real-time web search and content extraction to AI agents with the Parallel Search MCP Server
- [Task MCP](https://docs.parallel.ai/integrations/mcp/task-mcp.md): Enable deep research and data enrichment workflows in AI assistants with the Parallel Task MCP Server
- [n8n](https://docs.parallel.ai/integrations/n8n.md): Use Parallel in n8n Automations
- [OAuth Provider](https://docs.parallel.ai/integrations/oauth-provider.md): Integrate with the Parallel OAuth Provider to get a Parallel API key on behalf of your users
- [OpenAI Tool Calling](https://docs.parallel.ai/integrations/openai-tool-calling.md): Use Parallel Search as a tool with OpenAI's function calling to give GPT models real-time web access
- [Superhuman](https://docs.parallel.ai/integrations/superhuman.md): Use Parallel with Superhuman
- [Tempo & Machine Payments Protocol](https://docs.parallel.ai/integrations/tempo-mpp.md): Enable AI agents to make autonomous payments using Parallel and the Machine Payments Protocol via Stripe or Tempo stablecoins
- [Vercel](https://docs.parallel.ai/integrations/vercel.md): Use Parallel with Vercel
- [Zapier](https://docs.parallel.ai/integrations/zapier.md): Use Parallel in Zapier workflows
- [Events and Event Groups](https://docs.parallel.ai/monitor-api/monitor-events.md): Understand monitor events, event groups, and how to retrieve them
- [Monitor API Quickstart](https://docs.parallel.ai/monitor-api/monitor-quickstart.md): Track web changes continuously with scheduled queries and webhook notifications using the Monitor API
- [Simulate Event](https://docs.parallel.ai/monitor-api/monitor-simulate-event.md): Test your webhook integration by simulating monitor events
- [Slack Integration](https://docs.parallel.ai/monitor-api/monitor-slack.md): Set up Monitor in Slack to receive real-time web updates directly in your channels
- [Structured Outputs](https://docs.parallel.ai/monitor-api/monitor-structured-outputs.md): Return monitor events as structured JSON objects
- [Webhooks](https://docs.parallel.ai/monitor-api/monitor-webhooks.md): Receive real-time notifications for Monitor executions and detected events using webhooks
- [Changelog](https://docs.parallel.ai/resources/changelog.md): Product updates from the Parallel team
- [Crawler](https://docs.parallel.ai/resources/crawler.md): This documentation provides guidance for webmasters on managing their website's interaction with our crawling system
- [FAQs](https://docs.parallel.ai/resources/faqs.md): Frequently asked questions about Parallel APIs, billing, security, and platform features
- [Source Policy](https://docs.parallel.ai/resources/source-policy.md): Control which sources are used in web research, including domain allow/deny lists and a freshness start date.
- [Status Page](https://docs.parallel.ai/resources/status.md)
- [Warnings and Errors](https://docs.parallel.ai/resources/warnings-and-errors.md): Breakdown of warnings and errors
- [Webhook Setup](https://docs.parallel.ai/resources/webhook-setup.md): Guide to configuring and verifying webhooks for Parallel APIs
- [Search API Best Practices](https://docs.parallel.ai/search/best-practices.md): Using the Parallel Search API
- [Search Modes](https://docs.parallel.ai/search/modes.md): Configure the Search API mode for your use caseWhat is llms.txt?
llms.txt is an open standard that helps AI language models understand your website. By placing a structured markdown file at /llms.txt, websites provide AI search engines like ChatGPT, Claude, and Perplexity with a clear map of their content, services, and documentation. Companies like Parallel.ai use it to ensure AI accurately represents their brand when answering user queries. Read the spec.
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