Firecrawl API
65
AI ReadinessAI-Aware (B)65/100
Official vendor OpenAPI document · agent-readyData EnrichmentData Transformationhttp22 EndpointsREST
For Agents
Scrape, crawl, and map websites into clean markdown or structured JSON, extract fields with LLMs, run web search and deep research, and poll async job status.
Use for: Scrape this URL and give me the page as clean markdown, Crawl this documentation site and return every page's content, Map this domain so I know which URLs exist before scraping, Extract the product name, price, and rating from these pages
Not supported: Covers scraping, crawling, mapping, extraction, search, deep research, and job management. Billing, account provisioning, and dashboard settings are handled on the Firecrawl platform, not this API.
Firecrawl turns websites into clean, structured data for LLMs and agents. Point it at a single URL to scrape the page as markdown or JSON, crawl an entire site and its subpages, or map a domain to discover every reachable link. Beyond raw content it runs LLM-backed extraction to pull structured fields from pages, deep research over a query, web search with optional scraping of the results, and LLMs.txt generation for a site. Long-running scrape, crawl, extract, and research jobs are asynchronous: you start a job and poll its status endpoint for progress and results, with error and cancellation endpoints for each. Team endpoints report remaining credits and tokens so you can track usage.
Install Jentic One Beta
Connect the Firecrawl API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Firecrawl 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%2Ffirecrawl.dev%2Ffirecrawl" | 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%2Ffirecrawl.dev%2Ffirecrawl" | 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 Firecrawl API.
Scrape a single URL into markdown or structured JSON, with optional LLM extraction
Crawl a website and all reachable subpages, then poll the job for aggregated results
Map a domain to enumerate every discoverable URL before scraping
Extract structured fields from one or many pages using an LLM schema
Run web search and optionally scrape each result in the same call
Start deep research over a query and retrieve the synthesized findings
Generate an LLMs.txt file that summarizes a site for language models
Use Cases
Patterns agents use Firecrawl API for, with concrete tasks.
★ AI Agent Grounded in Live Web Content
A research or support agent needs current information that is not in its training data. Through Jentic it calls Firecrawl to scrape a specific page or search the web and scrape the results, receiving clean markdown it can read directly instead of raw HTML. The agent discovers the scrape and search operations by intent, so it fetches grounding content on demand without a developer wiring HTTP calls or parsing pages.
Search the web for a query, scrape the top three results into markdown, and summarize them with citations back to each source URL
Documentation and Knowledge-Base Ingestion
A team wants a whole documentation site turned into structured content for a RAG index. Firecrawl crawls the domain, follows subpages, and returns each page as markdown. Because crawls are asynchronous, the pipeline starts a crawl, polls its status until complete, and reads the aggregated pages, handling errors through the crawl errors endpoint.
Start a crawl of a docs domain, poll the crawl status until it finishes, and store each returned page as markdown for indexing
Structured Data Extraction at Scale
A pipeline needs specific fields from many pages, such as product name, price, and availability across a catalog. Firecrawl's extract endpoint takes a schema and uses an LLM to pull matching fields, and batch scrape processes many URLs at once. The workflow submits URLs, polls the extract or batch job, and receives normalized records ready to load.
Submit a list of product URLs to the extract endpoint with a name, price, and stock schema, poll the job, and return the normalized rows
Deep Research on a Topic
An analyst wants a synthesized answer that pulls from many sources. Firecrawl's deep research operation takes a query, searches and reads across the web, and returns findings the agent can present. The workflow starts the research job and polls its status endpoint until the synthesized results are ready.
Start a deep research job for a market question, poll until it completes, and return the synthesized findings with source links
Key Endpoints
22 endpoints — firecrawl turns websites into clean, structured data for llms and agents.
METHOD
PATH
DESCRIPTION
POST
/scrape
Scrape a single URL, optionally extracting fields with an LLM
POST
/crawl
Start a crawl across a site and its subpages
GET
/crawl/{id}
Get the status and results of a crawl job
POST
/map
Discover every reachable URL for a domain
POST
/extract
Extract structured data from pages using an LLM schema
POST
/search
Search the web and optionally scrape the results
POST
/batch/scrape
Scrape many URLs in one asynchronous job
POST
/scrape
Scrape a single URL, optionally extracting fields with an LLM
POST
/crawl
Start a crawl across a site and its subpages
GET
/crawl/{id}
Get the status and results of a crawl job
POST
/map
Discover every reachable URL for a domain
POST
/extract
Extract structured data from pages using an LLM schema
POST
/search
Search the web and optionally scrape the results
POST
/batch/scrape
Scrape many URLs in one asynchronous job
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.
F
Firecrawl API
- AI-Aware (B)65/100
74
Foundational Compliance70
Developer Experience & Jentic Compatibility48
AI-Readiness & Agent Experience94
Agent Usability60
Security60
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
97%
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.
70
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: A-Signals: 4
13%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
68%
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.
48
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: D+Signals: 4
42%
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.
52%
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.
60
Security
Trust, risk posture, and security compliance.
Grade: B-Signals: 1
60%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
60
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: C+Signals: 1
60%
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
Using Firecrawl by hand means managing async job polling, bearer-token auth, and the difference between scrape, crawl, extract, and search yourself. Through Jentic you install once, import the API from the Directory, and your agent calls the right operation and follows the job to completion.
Permission scoping
You choose which Firecrawl operations the agent may call, so a scraping task can be limited to POST /scrape and POST /search while crawl cancellation and feedback stay out of the allowed set. Rules run on your own instance and every call is logged.
Credential isolation
Your Firecrawl API key is stored once, encrypted, by your own Jentic One instance and injected as the bearer token at execution time, so it never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'scrape a URL to markdown' or 'extract structured data from pages', and Jentic returns the matching Firecrawl operation with its input schema so the agent calls the right endpoint without reading reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Firecrawl API through Jentic.
What authentication does the Firecrawl API use?
Per its OpenAPI spec every endpoint uses HTTP bearer authentication: you send your Firecrawl API key as a bearer token. Through Jentic that key is stored encrypted on your own instance and injected at call time, so it never appears in the agent's prompt or logs.
How do I scrape a website into markdown with the Firecrawl API?
Call POST /scrape with the target URL and Firecrawl returns the page as clean markdown or JSON. For a whole site use POST /crawl to start a job, then poll GET /crawl/{id} for the aggregated pages. Through Jentic you search for the intent 'scrape a URL' and the agent gets the operation and its input schema.
Are Firecrawl scrape and crawl jobs synchronous or asynchronous?
Scrape of a single URL returns directly, but crawl, batch scrape, extract, and deep research are asynchronous. You start a job and then poll its status endpoint, such as GET /crawl/{id} or GET /extract/{id}, until the results are ready, and each has matching error and cancel endpoints.
Can the Firecrawl API extract structured data, not just page content?
Yes. POST /extract takes a schema and uses an LLM to pull matching fields from one or many pages, and POST /scrape can extract fields from a single URL in the same call. This returns normalized records rather than raw HTML, which is what agents and data pipelines usually want.
What are the rate limits for the Firecrawl API?
The OpenAPI spec does not define numeric rate limits; usage is governed by your plan's credits and tokens, which you can read from GET /team/credit-usage and GET /team/token-usage. Check https://firecrawl.dev for current plan limits.
Can I limit what my agent is allowed to do with the Firecrawl API through Jentic?
Yes. You control which operations the agent may call, so you can allow POST /scrape and POST /search for read-style work while withholding cancellation and feedback endpoints. Every call the agent makes runs through your own instance and is logged, so its permissions stay under your control.
Is there a Firecrawl MCP server?
You don't need a separate MCP server to give your agent Firecrawl. Jentic connects it directly from the API Directory: import the API and your agent calls scrape, crawl, and extract on demand without loading another server's tool definitions into its context.
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