Parallel

Parallel.ai

High-accuracy web research API built for AI agents.

Setup

Install required Python packages:

pip install parallel-sdk requests

Set your API key:

export PARALLEL_API_KEY="your-key"

Get your key at: https://platform.parallel.ai

Optional — for authenticated source access (not required for basic usage):

export BROWSERUSE_API_KEY="your-key"  # Only if using authenticated sources

APIs Overview

Search API - Quick web search

python3 {baseDir}/scripts/search.py "Who is the CEO of Anthropic?" --max-results 5
python3 {baseDir}/scripts/search.py "latest AI news" --json

Task API - Deep research & enrichment

# Simple question → answer
python3 {baseDir}/scripts/task.py "What was France's GDP in 2023?"

# Structured enrichment (company research)
python3 {baseDir}/scripts/task.py --enrich "company_name=Stripe,website=stripe.com" \
  --output "founding_year,employee_count,total_funding"

# Research report (markdown with citations)
python3 {baseDir}/scripts/task.py --report "Market analysis of the HVAC industry in USA"

# With authenticated sources (requires browser-use.com key)
export BROWSERUSE_API_KEY="your-key"
python3 {baseDir}/scripts/task.py "Extract specs from https://nxp.com/products/K66_180"

Processors

FindAll API - Entity discovery (NEW Feb 2026)

Turn natural language into structured datasets. "Find all dental practices in Ohio with 4+ star reviews" → enriched list with citations.

# Basic entity discovery
python3 {baseDir}/scripts/findall.py "Find all AI startups that raised Series A in 2025"

# With enrichment
python3 {baseDir}/scripts/findall.py "portfolio companies of Khosla Ventures" \
  --enrich "funding,employee_count,founder_names" --limit 50

# Lead generation
python3 {baseDir}/scripts/findall.py "residential roofing companies in Charlotte, NC" --generator pro

# Check status of running job
python3 {baseDir}/scripts/findall.py --status findall_abc123

Generators

How it works

1. Ingest: Converts natural language → entity type + match conditions
2. Generate: Searches web for candidate entities
3. Evaluate: Validates each candidate against match conditions
4. Enrich: Extracts additional fields for matched entities

Extract API - Clean content extraction (NEW Feb 2026)

Convert any URL into clean markdown - handles JS-heavy pages, PDFs, paywalls.

# Basic extraction with excerpts
python3 {baseDir}/scripts/extract.py https://stripe.com/docs/api

# Full content (not just excerpts)
python3 {baseDir}/scripts/extract.py https://arxiv.org/pdf/2301.00000.pdf --full

# Focused extraction
python3 {baseDir}/scripts/extract.py https://sec.gov/10-K.htm --objective "Extract risk factors"

# Multiple URLs at once
python3 {baseDir}/scripts/extract.py https://url1.com https://url2.com --json

Use Cases

• API documentation - Pull complete references and code examples
• PDF research papers - Extract methodology, results, citations
• SEC filings - Extract specific sections from 10-Ks, earnings reports
• News articles - Get clean text without ads/nav/paywalls

Monitor API - Continuous tracking (NEW Feb 2026)

Set up recurring queries - get alerts when things change.

# Create a monitor
python3 {baseDir}/scripts/monitor.py create "Track AI funding news" --cadence daily
python3 {baseDir}/scripts/monitor.py create "Alert when AirPods drop below $150" --cadence hourly

# With webhook notifications
python3 {baseDir}/scripts/monitor.py create "OpenAI product announcements" \
  --cadence daily --webhook https://your-endpoint.com/webhook

# List all monitors
python3 {baseDir}/scripts/monitor.py list

# Get events (detected changes)
python3 {baseDir}/scripts/monitor.py events monitor_abc123
python3 {baseDir}/scripts/monitor.py events monitor_abc123 --lookback 10d

# Delete a monitor
python3 {baseDir}/scripts/monitor.py delete monitor_abc123

Cadences

• hourly - Fast-moving topics, stock/price tracking
• daily - News, competitive intel (most common)
• weekly - Slower changes, policy updates

Example queries

• News: "Let me know when someone mentions Parallel Web Systems"
• Competitive: "Alert me when Apple announces new MacBook models"
• Price: "Notify me when PS5 Pro is back in stock at Best Buy"
• Policy: "Track changes to OpenAI's terms of service"

Authenticated Sources (Jan 2026)

Task API supports authentication-gated private data sources via MCP servers:

• Internal wikis & dashboards
• Industry databases (NXP, IEEE, etc.)
• CRM systems & subscription services

Uses browser-use.com MCP integration:

Setup

1. Get API key from browser-use.com
2. Create a profile with saved login sessions
3. Set BROWSERUSE_API_KEY env var

Usage

export BROWSERUSE_API_KEY="your-key"
python3 {baseDir}/scripts/task.py "Extract migration guide from NXP K66 docs"

When to Use Each API

API Reference

• Docs: https://docs.parallel.ai
• Platform: https://platform.parallel.ai
• Changelog: https://parallel.ai/blog

Security & Permissions

What this skill does:

• Makes API calls to api.parallel.ai for web search, research, extraction, and monitoring
• monitor.py uses the requests library; all other scripts use the parallel-sdk package
• All scripts are read-only research tools — they do not modify any local or remote data
• The BROWSERUSE_API_KEY (optional) is only used for authenticated source access via api.browser-use.com

What this skill does NOT do:

• Does not send your API keys to any endpoint other than api.parallel.ai and api.browser-use.com
• Does not access local files, databases, or system resources
• Does not read config files or access the filesystem
• Does not write to disk (except JSON output when using --json)
• Cannot be invoked autonomously by the agent (disable-model-invocation: true)

Python dependencies: parallel-sdk, requests (install via pip install parallel-sdk requests)

Review scripts/ before first use to verify behavior.