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Parallel CLI
Command-line tool for web search, content extraction, data enrichment, deep research, entity discovery, and web monitoring
For AI agents: a documentation index is available at https://docs.parallel.ai/llms.txt. The full text of all docs is at https://docs.parallel.ai/llms-full.txt. You may also fetch any page as Markdown by appending
The .md to its URL or sending Accept: text/markdown.parallel-cli is a command-line tool for interacting with the Parallel API. It works interactively or fully via command-line arguments, making it the recommended way to use Parallel in standalone agents. For best results, pair the CLI with Agent Skills or Claude Code to give your agent structured access to search, extract, enrich, and research capabilities.
View the source and full README on GitHub.
Already have
parallel-cli installed? Run parallel-cli update to get the latest features and improvements.Installation
- pipx
- uv
- Homebrew
- pip
- npm
- Shell Script
Install in an isolated environment so
parallel-cli is on your PATH:pipx install "parallel-web-tools[cli]" && pipx ensurepath
pipx ensurepath is only required on first-ever pipx use; including it here makes the command safe to copy-paste either way. For the minimal CLI without YAML configs / interactive planner, use pipx install parallel-web-tools.uv is Astral’s faster modern alternative to pipx. It writes a PATH-aware shim on first run, so no ensurepath step is needed:uv tool install "parallel-web-tools[cli]"
uv to be installed first — see Astral’s install guide.brew install parallel-web/tap/parallel-cli
Use
pip when you’re embedding parallel-web-tools in a Python project (rather than using parallel-cli as a standalone tool — see the pipx tab for that):# Minimal SDK
pip install parallel-web-tools
# With YAML config files and interactive planner
pip install parallel-web-tools[cli]
# With data integrations
pip install parallel-web-tools[duckdb] # DuckDB
pip install parallel-web-tools[bigquery] # BigQuery
pip install parallel-web-tools[spark] # Apache Spark
# Everything
pip install parallel-web-tools[all]
npm install -g parallel-web-cli
Install the standalone binary (no Python or Node required):This detects your platform (macOS/Linux, x64/arm64) and installs to
curl -fsSL https://parallel.ai/install.sh | bash
~/.local/bin.Some agent skill registries flag the
curl | bash pattern as a supply-chain risk. If you’re installing parallel-cli for use with Agent Skills, prefer pipx or Homebrew.Authentication
# Interactive OAuth login (opens browser)
parallel-cli login
# Device authorization flow — for SSH, containers, CI, or headless environments
parallel-cli login --device
# Or set environment variable
export PARALLEL_API_KEY="your_api_key"
# Check auth status
parallel-cli auth
Get your API key from Platform.
Commands
Search
Search the web with natural language objectives or keyword queries.# Natural language search
parallel-cli search "What is Anthropic's latest AI model?" --json
# Keyword search with date filter
parallel-cli search -q "bitcoin price" --after-date 2026-01-01 --json
# Search specific domains
parallel-cli search "SEC filings for Apple" --include-domains sec.gov --json
# Set search mode
parallel-cli search "latest AI research" --mode turbo --json
| Option | Description |
|---|---|
-q, --query | Keyword search query (repeatable) |
--mode | turbo (fastest, ~200ms), fast (high-quality, ~700ms; recommended for most agents), basic (default; extended snippets per result), or advanced (highest quality). Deprecated Beta aliases map one-shot to basic and agentic to advanced |
--max-results | Maximum requested results (server default: 10) |
--include-domains | Only search these domains or domain/path prefixes (comma-separated or repeatable; paths require fast, basic, or advanced mode) |
--exclude-domains | Exclude these domains or domain/path prefixes (comma-separated or repeatable; paths require fast, basic, or advanced mode) |
--after-date | Only include results published on or after this date (YYYY-MM-DD) |
--excerpt-max-chars-per-result | Maximum excerpt characters per result |
--excerpt-max-chars-total | Maximum excerpt characters across all results (CLI default: 60,000) |
--max-age-seconds | Maximum cache age before fetching live content; values below 600 are adjusted to 600 with a warning |
--timeout-seconds | Timeout for fetching live content |
--disable-cache-fallback | Return an error instead of stale cached content when live fetch fails or times out |
--location | ISO 3166-1 alpha-2 country code for geo-targeted results |
--session-id | Group related Search and Extract calls in one session |
--client-model | Model generating the request and consuming the results |
--json | Output as JSON |
-o, --output | Save results to file |
Direct API calls use a dynamic total excerpt budget when
max_chars_total is omitted. The CLI sends 60000 by default unless --excerpt-max-chars-total is set.Extract
Extract clean markdown content from URLs.# Basic extraction
parallel-cli extract https://example.com --json
# Extract with a specific focus
parallel-cli extract https://company.com --objective "Find pricing info" --json
# Get full page content
parallel-cli extract https://example.com --full-content --json
| Option | Description |
|---|---|
--objective | Focus extraction on a specific goal |
-q, --query | Keywords to prioritize (repeatable) |
--full-content | Include complete page content |
--no-excerpts | Exclude excerpts from output |
--json | Output as JSON |
-o, --output | Save results to file |
Research
Run deep research on open-ended questions.# Run deep research
parallel-cli research run "What are the latest developments in quantum computing?" --json
# Use a specific processor tier
parallel-cli research run "Compare EV battery technologies" --processor ultra --json
# Read query from file
parallel-cli research run -f question.txt -o report
# Async: launch then poll separately
parallel-cli research run "question" --no-wait --json # returns run_id
parallel-cli research status trun_xxx --json # check status
parallel-cli research poll trun_xxx --json # wait and get result
# List available processors
parallel-cli research processors --json
| Option | Description |
|---|---|
-p, --processor | Processor tier: lite, base, core, pro (default), ultra, and -fast variants |
--no-wait | Return immediately after creating task |
--timeout | Max wait time in seconds (default: 3600) |
-o, --output | Save results (creates .json and .md files) |
--json | Output as JSON |
Enrich
Enrich CSV or JSON data with AI-powered web research.# Let AI suggest output columns
parallel-cli enrich suggest "Find the CEO and annual revenue" --json
# Run enrichment directly
parallel-cli enrich run \
--source-type csv \
--source companies.csv \
--target enriched.csv \
--source-columns '[{"name": "company", "description": "Company name"}]' \
--intent "Find the CEO and annual revenue"
# Enrich with inline data (no file needed)
parallel-cli enrich run \
--data '[{"company": "Google"}, {"company": "Apple"}]' \
--target output.csv \
--intent "Find the CEO"
# Enrich a JSON file
parallel-cli enrich run \
--source-type json \
--source companies.json \
--target enriched.json \
--source-columns '[{"name": "company", "description": "Company name"}]' \
--enriched-columns '[{"name": "ceo", "description": "CEO name"}]'
# Run from YAML config
parallel-cli enrich run config.yaml
# Async: launch then poll
parallel-cli enrich run config.yaml --no-wait --json
parallel-cli enrich status tgrp_xxx --json
parallel-cli enrich poll tgrp_xxx --json
| Option | Description |
|---|---|
--source-type | csv or json; Python installs with the relevant extras also support duckdb and bigquery |
--source | Source file path |
--target | Target file path |
--source-columns | Source columns as JSON |
--enriched-columns | Output columns as JSON |
--intent | Natural language description (AI suggests columns) |
--processor | Processor tier (e.g. core-fast, pro, ultra) |
--data | Inline JSON data array |
--no-wait | Return immediately |
--dry-run | Preview without making API calls |
--json | Output as JSON |
-o, --output | Save results to a JSON file |
--previous-interaction-id | Reuse context from a previous task |
YAML configuration format
YAML configuration format
You can also define enrichment jobs in YAML:Create YAML configs interactively or programmatically:
source: input.csv
target: output.csv
source_type: csv
processor: core-fast
source_columns:
- name: company_name
description: The name of the company
enriched_columns:
- name: ceo
description: The CEO of the company
type: str
- name: revenue
description: Annual revenue in USD
type: float
# Interactive
parallel-cli enrich plan -o config.yaml
# Non-interactive (for scripts/agents)
parallel-cli enrich plan -o config.yaml \
--source-type csv \
--source companies.csv \
--target enriched.csv \
--source-columns '[{"name": "company", "description": "Company name"}]' \
--intent "Find the CEO and annual revenue"
YAML config files and the interactive planner require
pip install parallel-web-tools[cli].FindAll
Discover entities from the web using natural language.# Discover entities
parallel-cli findall run "AI startups in healthcare" --json
# Control generator tier and match limit
parallel-cli findall run "Find roofing companies in Charlotte NC" -g base -n 25 --json
# Exclude specific entities
parallel-cli findall run "Find AI startups" \
--exclude '[{"name": "Example Corp", "url": "example.com"}]' --json
# Preview schema before running
parallel-cli findall run "Find YC companies in developer tools" --dry-run --json
# Fast, synchronous ranked entity search (no per-candidate verification)
parallel-cli findall entity-search "AI startups in San Francisco" \
--entity-type companies --match-limit 25 --json
# Async workflow
parallel-cli findall run "AI startups" --no-wait --json
parallel-cli findall status findall_xxx --json
parallel-cli findall poll findall_xxx --json
parallel-cli findall result findall_xxx --json
# Cancel a running job
parallel-cli findall cancel findall_xxx
| Option | Description |
|---|---|
-g, --generator | Generator tier: base, core (default), or pro |
-n, --match-limit | Max matched candidates, 5-1000 (default: 10) |
--exclude | Entities to exclude as JSON array |
--metadata | Run metadata as a JSON object |
--timeout | Max polling time in seconds (default: 3600) |
--poll-interval | Seconds between status checks (default: 30) |
--no-wait | Return immediately |
--dry-run | Preview schema without creating the run |
--json | Output as JSON |
-o, --output | Save results to a JSON file |
--dry-run calls the ingest endpoint to preview the generated schema. It does not create a FindAll run with the API’s preview generator.findall run normally ingests the objective, creates the run, applies enrichments suggested by ingest, and polls for results. With --no-wait, it returns after ingest and create; use findall enrich separately if you want to add enrichments to that asynchronous run.Monitor
Continuously track the web for changes.# Create a monitor
parallel-cli monitor create "Track price changes for iPhone 16" --json
# Set check frequency
parallel-cli monitor create "New AI funding announcements" --frequency 1h --json
# Track changes to a Task Run output
parallel-cli monitor create --type snapshot \
--task-run-id trun_xxx --frequency 1d --json
# With webhook delivery
parallel-cli monitor create "SEC filings from Tesla" \
--webhook https://example.com/hook --json
# Manage monitors
parallel-cli monitor list --json
parallel-cli monitor get mon_xxx --json
parallel-cli monitor update mon_xxx --frequency 1w --json
parallel-cli monitor cancel mon_xxx --json
# View events
parallel-cli monitor events mon_xxx --json
parallel-cli monitor events mon_xxx --event-group-id mevtgrp_xxx --json
# Run an off-schedule check
parallel-cli monitor trigger mon_xxx --json
trigger starts a real off-schedule run without changing the monitor’s regular frequency. It is not a synthetic webhook test, and cancelled monitors cannot be triggered. Cancellation is irreversible and permanently stops future runs; create a new monitor to resume monitoring.
| Option | Description |
|---|---|
-f, --frequency | Frequency in <n><unit> format using h, d, or w, such as 1h, 1d, or 1w (monitor create default: 1d). Aliases hourly, daily, weekly, and every_two_weeks are also accepted. |
--type | Monitor type for monitor create: event_stream tracks a search query (default); snapshot tracks a Task Run output |
--task-run-id | Task Run to track when creating a snapshot monitor |
--processor | Monitor processor for monitor create: lite (default) or the more thorough, higher-cost base |
--webhook | Webhook URL for event delivery |
--output-schema | Output schema as a JSON string (event_stream only) |
--status | Filter monitor list by active or cancelled; repeat to include both (default: active only) |
--event-group-id | Filter monitor events to a specific Monitor execution |
--json | Output as JSON |
Non-Interactive Mode
All commands support--json output and can be fully controlled via CLI arguments, making the CLI ideal for use in scripts and by AI agents.
# Structured JSON output
parallel-cli search "query" --json
# Read input from stdin
echo "What is the latest funding for Anthropic?" | parallel-cli search - --json
echo "Research question" | parallel-cli research run - --json
# Exit codes
# 0 = success, 2 = bad input, 3 = auth error, 4 = API error, 5 = timeout
Updating
The standalone binary automatically checks for updates and will notify you when a new version is available. To update:# pipx
pipx upgrade parallel-web-tools
# uv
uv tool upgrade parallel-web-tools
# Standalone binary
parallel-cli update
# Check for updates without installing
parallel-cli update --check
# Homebrew
brew upgrade parallel-cli
# npm
npm update -g parallel-web-cli
# pip
pip install --upgrade parallel-web-tools
parallel-cli config auto-update-check off
Assistant
Responses are generated using AI and may contain mistakes.