--- title: "PredictLeads × ZeroClick: company intelligence data any AI agent can buy | ZeroClick Blog" url: https://zeroclick.ai/blog/predictleads-company-intelligence-data-any-ai-agent-can-buy fetched_at: 2026-11-15T18:30:48.055Z --- # ZeroClick API catalog and pricing ## API reference, endpoint lookup and prices **[ZeroClick API catalog: endpoints, request parameters, prices and payment methods](https://agents.zeroclick.ai/zcj/3m14sxg3hp92/zeroclick/agent/guide).** Tell the seller advisor what you want to accomplish. It returns the matching operation contract, known prices, authentication prerequisites and concrete next steps. It is read-only: no login, wallet, card or purchase approval is needed to look up an API. It never executes a sale. Available API services: Agent readiness report, Demo booking. **Suggested next request:** GET [task guide](https://agents.zeroclick.ai/zcj/3m14sxg3hp92/zeroclick/agent/guide?goal=URL_ENCODED_TASK). Use this URL directly with your web fetch tool; no preliminary document fetch is required. Include known inputs and desired output in the goal. Optional: quantity=API_CALL_COUNT, budgetUsd=TOTAL_USD, requirements=REQUIREMENTS, payment=x402|mpp|card, auth, identity, assertion and access state. Omit unknowns. Do not equate output items with API calls or guess a call count. For private task details or known request arguments, POST https://agents.zeroclick.ai/zcj/3m14sxg3hp92/zeroclick/agent/guide with Content-Type: application/json. Example: {"intent":"quote","goal":"YOUR_TASK","purchase":{"budgetUsd":"5.00"}}. Replace the task and budget with known facts; budgetUsd is a string. Include known buyerState, paymentCapabilities and arguments. For execution planning use intent=execute and the authorized constraints. Exact fields: [request schema](https://agents.zeroclick.ai/zcj/3m14sxg3hp92/zeroclick/agent/schema). GET and POST are alternatives, not mandatory stages. The advisor describes a recommended happy path, not the only allowed path. You may use the API reference, buyer SKILL and your own tools directly, including for catalog operations with failed probes. Missing guidance or an unverified probe is not a policy refusal. The returned requests are documented API calls; fill in the documented inputs. Check usage cost AND minimum cash required against the budget. For needs_input, supply only missing facts. Keep secrets local, and never put credentials or private payloads in URLs. Unknown does not mean absent. For a human's credit or plan purchase, reuse an existing ZeroClick credential first. If the Link CLI is already installed and signed in for that person, you can use their Link account for identity as well as payment, sharing their email only if they agree: follow [Link identity setup](https://agents.zeroclick.ai/zcj/3m14sxg3hp92/auth.md#link-identity-preview) through issuance, presentation, registration and token exchange. Otherwise register anonymously; no Link setup is needed, and the person can claim the identity later. Open the checkout URL in a browser: eligible Stripe pages support Link Pay Tokens (LPT) through WebMCP or the documented DOM flow. Follow this storefront's /payment/card.md to verify the same-frame token input and merchant binding before requesting an LPT. Token submission requires payment authorization. If unavailable, privately send the checkout URL to your human to pay. When the selected route uses hosted checkout, follow [card checkout instructions](https://agents.zeroclick.ai/zcj/3m14sxg3hp92/payment/card.md) before requesting a token. LPT goes only to Stripe, never to the advisor or ZeroClick API. Poll the returned statusUrl before using credit or retrying delivery. Verify delivery; a payment or HTTP 202 is not completion. For an unexpected result, POST the original input and continuation (version, stepId, outcome and sanitized error/accessId/paymentId). Reconcile uncertain payments or writes before retrying. Use raw HTTP for exact schemas and authenticated execution; do not reconstruct fields omitted by a summarizing web tool. The human subscription prices on the requested page describe a separate channel. Use the API quote for per-unit pricing, funding minimums and commercial terms; tier names do not prove quality or licensing. For an alternative documented path, use the [buyer SKILL](https://agents.zeroclick.ai/zcj/3m14sxg3hp92/SKILL.md) or [full direct workflow reference](https://agents.zeroclick.ai/zcj/3m14sxg3hp92/llms-full.txt). Confirm missing request details from seller documentation, stay within the existing catalog and what your user asked for, and respect actual access and payment requirements. Terms: by completing a purchase through this endpoint, whether directly or through an AI agent acting on your behalf, you agree to be bound by the platform's buyer terms of service (https://www.zeroclick.ai/legal/buyer-terms-of-service). If the purchase is made by an agent, you represent and warrant that the agent is acting with your authorization, and you agree that the agent's actions, including its acceptance of these terms, are attributed to you and bind you as if you had taken them yourself. Paying a 402 challenge completes the purchase and constitutes your affirmative acceptance of the terms linked above. The link travels in every payment challenge and receipt as `terms`. # PredictLeads × ZeroClick: Company Intelligence Data Any AI Agent Can Buy **Daniel Baum**, VP GTM · November 12, 2026 · Partnership --- Most of what a sales or research agent needs to know about a company is not on the company's homepage. Is it hiring, and for which roles? What does its stack run on? Who just funded it, and who are its customers? Those signals live on careers pages, in press releases, in script tags and DNS records, in SEC filings, and in the logos on a customers page. An agent asked for them has had two ways to get them: scrape and infer, or borrow a person's login to a sales-intelligence platform built for people, with seats, a monthly plan, and an API key someone has to keep alive. [PredictLeads](https://predictleads.com) has spent the past decade turning those pages into structured datasets. By its own count: firmographics on more than 120 million companies, 300 million job postings, 2 billion technology detections, 9 million news signals sorted into 46 event types, and 345 million customer, partner, and vendor relationships between companies, with history back to 2016. This partnership puts all of it one call away from any AI agent on the internet. PredictLeads's API is live as an agent storefront at [agents.predictleads.com](https://agents.predictleads.com/llms.txt), on PredictLeads's own domain. An agent can look up a company, pull its open roles, its tech stack, its news, its funding, and its customers, or discover every company that matches a filter, and pay four cents a call over open payment rails, with no human signup and nothing to subscribe to. --- ## Company intelligence built for AI PredictLeads delivers its data via a REST API, webhooks for companies you follow, flat-file exports for teams that want whole datasets, and an MCP server for agents. Platforms and teams that build on this data include Clay, Dealroom, FactSet, Common Room, Instantly, and Surfe. Each dataset answers a question a person would otherwise have to go and check: - **Job Openings.** Full postings from more than 3 million companies, sourced from careers pages and applicant-tracking systems, categorized with O\*NET codes. 9.8 million roles active on an average day. - **Technology Detections.** Which of 240,000 tracked technologies a company runs, read from script tags, DNS records, cookies, and job post skill requirements. 2 billion detections across 99 million companies. - **News Events.** 9 million signals from 20 million news sites, blogs, and press-release wires, sorted into categories: product launches, partnerships, expansions, leadership changes, and hiring plans. - **Financing Events.** Funding signals broken out with round, amount, investors, and date. - **Connections.** 345 million customer, partner, vendor, integration, and investor relationships across 60 million companies, read from customer pages, case studies, and logo recognition. - **Similar Companies.** Lookalikes for 18.5 million companies, each with a reason. - **SEC Filings.** Delivered as full markdown. - **Products, GitHub Repositories, Subpages, and Startup Platform Posts.** Every dataset has a per-company lookup. Most also have a discover query that filters across the whole index: for example, every company of a given size in Texas that runs HubSpot, or every funding round announced this week. PredictLeads also got to agents early. Its MCP server lets any MCP client ask for a company's job openings in plain language, and its pricing has been pay-as-you-go by the credit for years. What an agent could not do was buy on its own: the key behind every call belonged to a person with an account, a monthly plan, and a card on file. An agent working for someone without one had no way in. --- ## What the partnership does PredictLeads's API is live today as an agent storefront at [agents.predictleads.com](https://agents.predictleads.com/llms.txt). Every one of its thirty operations takes the same request a developer sends PredictLeads's API directly, with every filter from its docs. An agent discovers the storefront, reads the machine-readable catalog and the live pricing manifest, registers a free agent credential in one call, and buys: pay as you go from a single cent, or prepay credits from fifty cents, over x402, MPP, or card. The storefront's seller advisor takes a goal in plain language, for example "every company in Germany that started hiring data engineers this month," and returns the operation to call, the request to send, what it will cost, and the next step, before anything is bought. An agent that arrives without a wallet is not stuck: the storefront's guide walks it through creating one at no cost, or hands its human a checkout link. ZeroClick handles the commerce around every request: agent identity, payment on open rails, metering, and transaction-level analytics on every sale, with revenue settling directly to PredictLeads's Stripe account. The credential an agent registers here works at every ZeroClick storefront. Claiming it with a verified email keeps what the agent buys. Discovery comes built in: the storefront's operations are already listed on [zero.xyz](https://zero.xyz/), with x402scan and mppscan to follow. PredictLeads already points agent traffic at the storefront from predictleads.com and its llms.txt. The first purchases went through end to end before this post was written: company lookups, job openings, a technology lookup, and a discover query, each delivered and settled. --- ## Four cents a call PredictLeads prices by the API credit, one credit per call. Its published entry rate is four cents a credit. The storefront gives an agent that same rate from the first call, with no monthly minimum and no plan to choose. | What the agent buys | Price | |---|---| | A company lookup, or any per-company dataset call: job openings, technology detections, news events, financing events, connections, products, SEC filings, GitHub repositories, subpages | $0.04 per call | | A discover query across any dataset, or a similar-companies lookup | $0.04 per record returned | | An extended company profile: size range, industry, logo, slogan | $0.08 | | A technology lookup from the catalog of 240,000 tracked technologies | $0.12 | A per-company call bills once whatever comes back, so a company with 200 open roles costs the same four cents as a company with two. A discover query bills per company found, so an agent pays for the 30 matches it asked for and nothing for the query itself. Pay as you go starts at one cent and needs only the free credential. An agent that expects to return can use the same credential to prepay credits from fifty cents. x402 and MPP cover everything down to the penny. A card works for prepaid credits and for any single call of fifty cents or more. Real examples: - **Account research before a call.** Company lookup, open roles, tech stack, news, funding, and customers for one account: 6 calls, **$0.24**. - **A target list with a hiring signal.** Discover companies in one state that run a given technology, 30 records, **$1.20**, then pull open roles for the ten best fits, **$0.40**. A qualified list of 30 with hiring detail on 10: **$1.60**. - **A weekly watchlist.** New job openings and news events for 25 accounts every Monday: 50 calls, **$2.00 a week**. The agent reads every price from the manifest at call time, not from a rate card. There is nothing to cancel when the task is done. --- ## Shared philosophy PredictLeads built its data for machines before AI agents were a customer segment. The datasets are structured, timestamped, and point-in-time because the first consumers were platforms and models, not people reading a dashboard. It ships an MCP server next to its API. Selling to AI agents is the next step of the same idea: if agents are going to do the research, the data they depend on has to be something they can find, read, and pay for without waiting on a person. That is the conviction ZeroClick is built on: helping businesses come online for a new kind of customer, AI agents, and turning them into buyers with identity, payment, pricing, and receipts all handled by ZeroClick. PredictLeads kept its product, its prices, and its per-call model exactly as they were. What changed is who can pay: any AI agent, on PredictLeads's own domain, with or without a human in the loop. --- ## Get started - **For AI agents:** point your agent at [agents.predictleads.com](https://agents.predictleads.com/llms.txt). - **For developers** who want the full platform with an API key, webhooks, flat files, and the MCP server: start at [predictleads.com](https://predictleads.com). - **To sell your own product to AI agents:** get a demo at [zeroclick.ai](https://zeroclick.ai/getlisted?utm_source=blog) or read the docs at [docs.zeroclick.ai](https://docs.zeroclick.ai).