Official vendor OpenAPI document · agent-readyAI/MLEmbeddings SearchapiKey37 EndpointsREST
For Agents
Search the web or extract content from URLs, run deep-research tasks with structured outputs, find all entities matching conditions, and set up monitors that watch web content for changes, all through Parallel.
Use for: Search the web for recent news on solid-state battery suppliers, Extract the pricing details from these three product pages, I need a structured research report on a company's funding history, Find all Series A fintech startups in Berlin
Not supported: Does not crawl whole websites, host your documents for retrieval, or train models. Use for web search, extraction, research tasks, entity discovery, and web change monitoring only.
The Parallel API searches and researches the web for AI applications. Its Search and Extract operations return relevant web content for a set of search_queries or specific urls, and image search finds images on the web. Task runs take an input and a processor such as lite, base, core, or pro and return structured, research-backed results, with task groups for running many inputs together, while FindAll runs discover entities that match stated conditions and Monitors re-run searches or tasks on a fixed frequency to detect changes. A Responses operation and a chat completions endpoint return answers grounded in live web research with URL citations.
Install Jentic One Beta
Connect the Parallel API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Parallel API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fparallel.ai%2Fparallel" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fparallel.ai%2Fparallel" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Parallel API.
Search the web for a list of search_queries with an optional objective and character budget through /v1/search
Extract the content relevant to an objective from specific urls through /v1/extract
Run a research task with a processor and input, then poll its status or stream events and fetch the result from /v1/tasks/runs/{run_id}/result
Batch many task runs into a task group and fetch all of the group's runs
Discover entities matching an objective, entity_type, and match_conditions with a FindAll run, then extend or enrich the results
Create monitors of type event_stream or snapshot that run on a frequency and report changes through events or a webhook
Get answers grounded in live web research with URL citations from /v1/responses
Use Cases
Patterns agents use Parallel API for, with concrete tasks.
★ Web research for agents through Jentic
An agent that needs current facts calls Parallel's search or responses operation through Jentic instead of relying on its training data. It sends search_queries with an objective, receives relevant excerpts, and cites the source URLs in its answer. Your own Jentic One instance injects the x-api-key header value at call time, so the agent never sees the key.
POST /v1/search with objective 'find recent suppliers of solid-state batteries' and search_queries ['solid-state battery supplier 2026', 'solid-state battery partnership announcement'], then summarise the results with their URLs
Structured research task runs
Teams that need the same research done for many inputs, such as profiling companies from a list, create task runs with a processor and input and a task_spec for the output shape. Runs return immediately in status queued; the agent polls the run or streams its events and then reads the result, and task groups track many runs together.
POST /v1/tasks/runs with processor 'core' and input 'Acme Robotics funding history', then GET /v1/tasks/runs/{run_id}/result once the run completes
Entity discovery with FindAll
Lead lists and market maps start with finding every entity that fits. A FindAll run takes an objective, entity_type, match_conditions, generator, and match_limit, returns a queued run, and its result endpoint returns the matched entities; extend adds more matches and enrich adds fields to them.
POST /v1beta/findall/runs with objective 'Series A fintech startups in Berlin', entity_type 'company', match_conditions for funding stage and location, a generator, and match_limit 50, then GET /v1beta/findall/runs/{findall_id}/result
Change monitoring on web content
Monitors re-run a search query or a task's output on a fixed frequency and report material changes, so a competitive-intelligence agent learns about new announcements without polling. A monitor takes a type, frequency, and settings, can post to a webhook, and lists its events, and it can be triggered on demand or cancelled.
POST /v1/monitors with type 'event_stream', frequency '1d', and settings for the query 'Acme Robotics announcement', then GET /v1/monitors/{monitor_id}/events the next day
Key Endpoints
37 endpoints — the parallel api searches and researches the web for ai applications.
METHOD
PATH
DESCRIPTION
POST
/v1/search
Search the web
POST
/v1/extract
Extract content from URLs
POST
/v1/tasks/runs
Create a task run
GET
/v1/tasks/runs/{run_id}/result
Retrieve a task run result
POST
/v1beta/findall/runs
Create a FindAll run
POST
/v1/monitors
Create a monitor
POST
/v1/responses
Create a web-grounded response
POST
/v1/search
Search the web
POST
/v1/extract
Extract content from URLs
POST
/v1/tasks/runs
Create a task run
GET
/v1/tasks/runs/{run_id}/result
Retrieve a task run result
POST
/v1beta/findall/runs
Create a FindAll run
POST
/v1/monitors
Create a monitor
POST
/v1/responses
Create a web-grounded response
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
P
Parallel API
- AI-Aware (B)64/100
74
Foundational Compliance64
Developer Experience & Jentic Compatibility49
AI-Readiness & Agent Experience94
Agent Usability50
Security74
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.2
Show dimension breakdown
74
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: A-Signals: 4
96%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
0%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
100%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
64
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: BSignals: 4
7%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
50%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
49
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: D+Signals: 4
45%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
51%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
50
Security
Trust, risk posture, and security compliance.
Grade: C-Signals: 1
50%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
74
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A-Signals: 1
74%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring Parallel by hand means the x-api-key header, the parallel-beta header for beta features, and polling or streaming asynchronous task and FindAll runs. Through Jentic you install once, import Parallel from the API Directory, store the key once, and your agent calls it.
Permission scoping
Parallel puts run, task group, FindAll, and monitor ids in the URL path, such as /v1/monitors/{monitor_id}, so a rule can pin your agent to one monitor or one run. You choose the operations it may call, so costly or destructive ones like task runs or memory clear are not included unless you add them.
Credential isolation
Your Parallel API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'search the web' or 'run a research task', and Jentic returns the matching Parallel operation with its input schema so the agent sends the right processor and inputs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Parallel API through Jentic.
What authentication does the Parallel API use?
The Parallel API authenticates with an API key sent in the x-api-key header per its OpenAPI spec. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at call time, so it never enters the agent's prompt or logs.
What is the difference between Search and Task runs in the Parallel API?
POST /v1/search returns relevant web excerpts for your search_queries in a single call. POST /v1/tasks/runs starts an asynchronous research job with a processor such as lite, base, core, or pro and returns a run in status queued; you then poll it, stream its events, or wait for a webhook, and read the structured result.
Can I get notified when a task run finishes?
Yes. Task runs, FindAll runs, and monitors accept a webhook in the request body, and task runs and FindAll runs also expose event streams at their events endpoints, so an agent does not have to poll for completion.
What are the rate limits for the Parallel API?
The OpenAPI spec does not specify rate limits. Check the Parallel documentation at docs.parallel.ai for current limits.
How do I run a web search through Jentic?
Install Jentic One, add the Parallel API from the Jentic API Directory, and store your Parallel API key once. Your agent searches for 'search the web for current information', gets the search operation with its input schema, and calls POST /v1/search with search_queries and an objective. To run it on your own infrastructure, install Jentic One from its GitHub repo.
Is there a Parallel MCP server?
You don't need an MCP server to give your agent the Parallel API. Jentic connects it directly from the API Directory: import it, store your credential once, and your agent calls it, finding operations on demand rather than loading extra tool definitions.
Can I limit what my agent is allowed to do with the Parallel API?
Yes. Write a rule that allows only POST /v1/search and POST /v1/extract, and your agent can search and read web pages but cannot start paid task runs, create monitors, or clear memory. Your own Jentic One instance logs what it called.
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