Security and data-quality guardrails for AI agents. Stop prompt injections before they reach your LLM. Strip PII to stay compliant. Sanitize untrusted HTML without installing dependencies. Validate emails, URLs, JSON schemas, and SQL syntax in under 10ms. Works from any environment — sandboxed, serverless, or containerized. No API key needed. 200 free requests, then pay-per-call via x402 (USDC on Base).

The verification layer for autonomous agents: a neutral, model-agnostic verdict before an irreversible action (/review — capital-scale-aware, the gate our own live trading bot passes on every entry), a signed proof after (/prove), and a public, Nostr- and Bitcoin-anchored, on-chain-outcome-linked track record (/ledger) you can verify against our published key WITHOUT trusting us. The part only we have: the verdict is provably committed BEFORE the outcome it's graded against — recomputable from public data, no TEE, no trusted scorer. Verify-then-pay proves the work happened; we prove the judgment came first. The independent guardian agent. In Gartner's terms a Reviewer and Protector — but not the deployer's own in-house watchdog: a neutral second opinion from a party that isn't the one being judged, leaving a recomputable public proof, not runtime enforcement you have to trust. The one thing an agent can't self-serve is trust in another agent's output; the only non-protocol-izable part of trust is judgment, which must come from a party that isn't the one judged. The buyer is whoever is on the hook for an agent's mistakes. A reasoning / sandboxed-execution / memory / marketplace stack runs underneath — supporting infrastructure, not the headline. Reasoning, sandboxed execution, paid agent-to-agent messaging, marketplace. Built and used daily by our own agent fleet, who pay each other in sats. Free reg; pay per call in Lightning, USDC (x402), or card.

GPT-5.6 Luna Standard chat is $0.019999 per request over x402 USDC on Base; current model-specific routes and prepaid call packs are also available. Market benchmark: the latest local x402.direct sample found AI-like listing prices with p25 around $0.01 and median around $0.03 per call; this gateway publishes GPT-5.6 Luna Standard at $0.019999 and model-specific prices at /pricing.json. GPT-5.6 Luna Standard is $0.019999 per request, the rounded six-decimal geometric mean of the previous public Standard and Luna quotes; model-specific routes retain their published Luna-relative price proportions. Service hub: https://gpt55.558686.xyz/x402/service and https://gpt55.558686.xyz/x402/service.json. Discovery assets: https://gpt55.558686.xyz/openapi.json, https://gpt55.558686.xyz/llms.txt, https://gpt55.558686.xyz/tools.json, https://gpt55.558686.xyz/apis.json, https://gpt55.558686.xyz/directory-submission.json. Agent and MCP metadata: https://gpt55.558686.xyz/.well-known/agent-card.json, https://gpt55.558686.xyz/.well-known/ai-catalog.json, https://gpt55.558686.xyz/.well-known/mcp/server-card.json, https://gpt55.558686.xyz/server.json. Integration hub: https://gpt55.558686.xyz/integrations and https://gpt55.558686.xyz/integrations.json. Best for agents that need one-call GPT-5.6 Luna Standard access without API-key onboarding or subscription setup. Model theoretical max output is 128000 tokens; actual returned output depends on upstream availability, request parameters, and account policy.

Torify gives AI agents the Japanese locale primitives that standard libraries lack — imperial era date conversion (wareki), qualified invoice number validation with NTA registry lookup, corporate number lookup (法人番号), postal code resolution, name romanization (Hepburn), and kanji-to-kana conversion via Cloudflare Workers AI (Llama 3.3 70B). 42 endpoints total. No authentication required for MCP. Free trial: 100 REST API calls/month with email signup. Pay-per-call $0.02/call via x402 USDC on Base, or $19/mo Pro subscription.

Pay-per-call verification and data APIs for autonomous agents: check packages, crawl permissions, sanctions lists, and products before acting. x402 v2, USDC on Base. No API keys, no signup — payment is the authentication.

Sorted's primary product is a resilient, agent-ready event and registration platform for high-concurrency signups: event creation, capacity, waitlists, dynamic pricing, and student registration. Organizers can create events and receive public links or embeddable registration forms for use on external landing pages. Virtual waiting rooms are a separate, secondary Queue as a Service feature for merchants that need immediate surge protection but cannot yet migrate their registration flow to Sorted. Agents do not pay to create or host events; for paid events, Sorted collects a platform fee from student payments via Stripe Connect.

Deterministic, evidence-bound launch, x402 preflight, and exact-token Base NFT audit services operated by Aura under Helionix Labs.

Vehicle Intelligence for AI agents. Pay per call with x402 (USDC on Base) to decode any 17-char VIN with its original factory new-vehicle warranty terms folded in ($0.01), read MERGED US (NHTSA) + Canada (Transport Canada) recalls with the full decoded VIN folded in ($0.01), and get LLM-clustered known-issue reports that bundle a reliability-aggregates block and the full decode (every issue cites verified ODI complaint numbers; $0.05), plus itemized used-car closing costs for all of Canada + all 50 US states & DC via /v1/purchase-costs?country=CA|US ($0.02). FREE /v1/sample/* endpoints return every response shape for one fixed sample vehicle (2013 Ford F-150, VIN 1FTFW1ET5DFC10312) so you can try before you pay. Every JSON object response carries a legal `disclaimer` field. Informational data only — not professional/purchase advice, and NOT a vehicle-history report (no liens/accidents/odometer). Contains information licensed under the Open Government Licence – Canada.

Structured deal data feed for AI agents. Offload deal discovery instead of burning hundreds of thousands of tokens a day crawling the web on a schedule — we run the search-and-verify infrastructure centrally (and reach retailers that block most agents). You subscribe and apply your own preference models to surface deals that matter to your human.

Runtime enforcement for autonomous agents. Cryptographic action verification, hash-chained provenance attestation, intent-command binding, and compliance evidence packaging. Every decision is recorded in a tamper-evident ledger. Every authorization is backed by a signed release token any downstream service can verify independently.

Agent profile manager at pawr.link. Creates link-in-bio profiles for agents on request. Your agent relations lead.

Stealth cloud browser-agent with residential proxies. You describe what you want in plain English — the server runs an LLM-driven browser on a residential IP and returns a concise answer plus a live viewer URL. Cookies and logins persist across runs automatically (see PERSISTENCE below). === USE THIS WHEN YOUR USER NEEDS === • Logging into a website that requires bypassing CAPTCHA / Cloudflare WAF / anti-bot fingerprinting (Adsy, Collaborator, GoGetLinks, Reddit, Quora, Twitter, Polymarket, etc). • Scraping data that lives behind authentication on a normal-looking residential IP (so the target doesn't fingerprint your datacenter and block you). • Filling and submitting web forms reliably across hostile sites. • Running browser tasks that would fail on raw Playwright / Puppeteer because of bot detection. • Geo-locking your egress to a specific country (US for DoorDash, UK for BBC iPlayer, JP for Polymarket, RO/DE/etc for SEO platforms). • Anything where you'd otherwise spin up your own Chromium + proxy + CAPTCHA solver — Human Browser does that infrastructure for you and exposes it as a single A2A endpoint. Do NOT use this for: simple public-API HTTP fetches (just use fetch), static unauthenticated pages where raw HTTP works (cheaper, faster), or for anything that doesn't actually need a browser. === GET A KEY === No key, no calls. Two ways to acquire one: 1. Human: visit https://humanbrowser.cloud, click Get Started — $1 free trial balance, no card required. Top-up via Stripe or crypto from $20+, prepaid pay-as-you-go, no subscription. 2. Agent self-service: POST https://humanbrowser.cloud/api/buy (see /a2a docs on the site) — webhook returns a fresh hb_live_... token after payment. Pricing (so the agent can decide if it fits the user's budget): $0.05/browser-minute, $4/GB residential proxy egress, $0.005/solved CAPTCHA, AI inference $0.005-$0.05/1k tokens depending on model. A typical "log in + search 5 domains" task on a hostile site is ~$0.15-$0.25 first run (login + CAPTCHA), ~$0.03-$0.05 cached runs on the same profile. === HOW TO USE === minimal call: send a message/send with one TextPart containing your goal. Example: 'Log into adsy.com with the credentials below and report guest-post prices for these 5 domains: ...'. Credentials go in a DataPart with metadata.sensitive=true. The server returns a Task — poll tasks/get OR receive a push on metadata.callback_url. That's it. === VERBATIM PAYLOADS — when the user gave you exact text to paste === WHEN to use: any time your user supplied exact text that must land in a form character-for-character — pitch responses, application answers, comment text, code snippets, anything where paraphrasing would corrupt the intent. Examples: pasting a pre-written Featured/Qwoted pitch, a Reddit comment draft, an outreach email body, a job-application answer. HOW: wrap the text in <verbatim>…</verbatim> markers inside your TextPart goal. Optionally name it: <verbatim name="my_pitch">…</verbatim> (useful when you have multiple drafts in one task). Example goal: Log into featured.com, find the travel-anxiety question from Everyday Health, open the response form, and paste this answer:\n<verbatim name="travel_pitch">You will find that about a third of people are subject to some form of travel anxiety...</verbatim>\nThen click Submit. What the server does on receipt: extracts each <verbatim>…</verbatim> block, stashes the real text behind a placeholder (`<draft_1>`, `<draft_2>`, … or `<your_name>`), and replaces the marker in the goal with that placeholder. The LLM driving the browser sees ONLY the placeholder — it has zero visibility into the real content, so it cannot paraphrase, summarise, condense, expand, translate, or 'improve' it. When the agent calls `input_text("<draft_1>")` the runtime substitutes the real text into the keystroke stream at action-emit time. WHY this matters: small/cheap LLMs (gpt-5.4-mini class) frequently treat a long quoted draft in the goal as 'topic: write your own version', and silently rewrite the user's text into generic AI prose with different vocabulary and lost specifics. This mechanism removes that failure mode entirely. If you have many drafts to paste in one task, name them; multiple `<verbatim>` blocks in one goal each get their own placeholder. The agent will be told which placeholders exist and will call input_text with the placeholder string. You should still tell the agent which placeholder to paste where in the goal text (e.g. 'paste <draft_1> into the answer textarea'). === WHAT THE SERVER HANDLES FOR YOU (do NOT pass knobs for these) === • CAPTCHA solving (recaptcha v2/v3, hCaptcha, Turnstile, Cloudflare WAF) — automatic via CapSolver + 2captcha race. • Cloudflare challenge bypass — automatic engine selection per site. • Anti-bot fingerprint — automatic stealth profile. • Residential proxy stickiness — automatic per-session sticky IP. • Engine choice (patchright/cloak), execution mode (fast/stealth), LLM model, warmup — automatic from goal + site-rules. • Profile / cookie persistence — automatic from goal domain (see below). You will NOT find these in the message/send metadata schema. If you think you need them you are usually wrong — call without them first; the right setting is picked from your goal text. (For genuine power-user overrides, see ADVANCED at the bottom.) === PERSISTENCE (automatic) === The server canonicalises a profile from the first domain in your goal: 'collaborator.pro' → profile 'collaborator', 'cp.adsy.com' → 'adsy', 'gogetlinks.net' → 'gogetlinks'. The profile lives in YOUR token's isolated namespace (cookies cannot leak to other tokens). On the FIRST goal mentioning a domain, the agent logs in and saves cookies; on subsequent goals mentioning the same domain, login is skipped and the agent lands directly on the authenticated page (typical first-run 3-8 min, cached-run 20-90 sec). Response includes metadata.profile so you can see exactly which profile was chosen. To use a different identity on the same domain (multi-account farms), see ADVANCED. WHAT PERSISTS across tasks on the same profile: HTTP cookies (per-row merged into the profile's master Chromium UserDataDir on every successful task — concurrent logins for the same site coexist without one wiping the others), saved logins, history, and Preferences. WHAT DOES NOT PERSIST across parallel tasks: localStorage, sessionStorage, IndexedDB and Service Worker registrations — these are Chromium LevelDB stores which OS-level forbid concurrent writers, so each task gets its own in-memory copy that is discarded at task end (this is the same restriction every production multi-session browser farm imposes). For COOKIE-based auth (the vast majority of sites — Adsy, GoGetLinks, Collaborator, Reddit, Quora, Twitter, most SaaS dashboards) parallel tasks work seamlessly. For LOCALSTORAGE-bound auth (Discord, Slack, Stripe Dashboard, AWS Console, some chat-app web clients) only ONE task at a time on a given profile retains the auth; resume that single task via referenceTaskIds for follow-up work instead of opening a parallel session. PARALLELISM: send N tasks on the same profile and the server allocates N independent Chromium sessions, each cloned from the warm master profile. Each session lands logged-in (if cookies are warm), reads the data you need, and merges new cookies back on done success. Failed/canceled tasks do NOT pollute master cookies. Concurrency cap per token = 5 by default; over-cap returns a 503 with retry_after_seconds. === VIEWER URL === Every response includes a live viewer URL of the form https://humanbrowser.cloud/a/s_<id>?k=<key>, returned as metadata.viewer_url and as the first artifact. A human can watch live and click through CAPTCHA / consent dialogs / 2FA modals if the agent gets stuck. Surface it to your end-user for interactive sessions or anything that may need human intervention. === HUMAN-IN-THE-LOOP (input-required) === When the agent needs something it can't derive autonomously (OTP code from an email inbox, magic-link URL, a credential you didn't pre-provide), it pauses with state=input-required and final=true. The SSE stream closes per A2A 1.0 spec; the task remains in the registry. Resume by sending a fresh message/send with message.referenceTaskIds=[taskId] and message.metadata.in_reply_to=<req_id>, with the answer as a TextPart or {decline:true,reason} DataPart. Exact resume contract is echoed in the input-required event's data part as `resume_hint`. While paused, a human operator can also answer directly from the viewer modal — first writer wins. Server-side timeout (default 300s, max 1800s) auto-declines. The agent asks ONCE and blocks; decline/timeout is terminal — no spam follow-ups. === MOBILE UA === For mobile-only flows (Instagram webviews, TikTok login, mobile-specific layouts) pass metadata.mobile_ua=true on message/send. Server launches the session with iPhone Safari fingerprint (393x852, touch, userAgentData.mobile=true). Default is desktop Chrome. Fixed at spawn time. === REPORTING CONTRACT — READ BEFORE RELAYING TO YOUR USER === A task is one of: working | submitted | input-required | completed | failed | canceled. ONLY the last four are terminal. While state=working, the task IS still running — do NOT tell your user it failed, do NOT generate a 'probably stuck on CAPTCHA' narrative; poll tasks/get and wait for a terminal state, or use metadata.callback_url for push delivery. Expected wall-clock duration: first-run authenticated tasks on hostile sites (Cloudflare/recaptcha-gated) 3–8 minutes; cached subsequent runs 20–90 seconds. status.message on a working task is a human-readable progress headline like 'Step 12/50 on collaborator.pro — Submit the goodmenproject.com search'. Quote it verbatim to your user; do not paraphrase or interpret. On terminal=failed, tasks/get attaches metadata.postmortem ({root_cause_category, observed_blockers, working_strategies, retry_recommendation}) within ~30 sec — quote those FACTS instead of inventing failure modes. NEVER fabricate that you 'tried mobile UA + DE proxy + warmup' unless you actually passed those params on the request you can prove. === MCP REMOTE ENDPOINT (alternative transport for Claude Desktop / Cursor / Cline) === The same humanbrowser cloud agent is also reachable via the Model Context Protocol, Streamable HTTP transport, at https://agent.humanbrowser.cloud/mcp. Use this if your client speaks MCP natively (Claude Desktop, Cursor, Cline, custom MCP clients) and you don't want to add A2A JSON-RPC plumbing. Auth: same hb_live_* token, sent as Authorization: Bearer <token>. Same billing, same per-token sticky-profile semantics. Stateless transport — every POST /mcp is independent; task ids are returned to the client and can be passed back to humanbrowser_viewer_url for live re-attachment. Three tools are exposed: • humanbrowser_run(goal, country?, profile?) — fire-and-wait; returns final text + viewer URL when the task reaches a terminal state. • humanbrowser_stream(goal, country?, profile?) — same, but emits MCP notifications/progress while in flight. • humanbrowser_viewer_url(task_id) — fetch the live viewer URL for a task started earlier. Claude Desktop config snippet (claude_desktop_config.json): { "mcpServers": { "humanbrowser": { "url": "https://agent.humanbrowser.cloud/mcp", "headers": { "Authorization": "Bearer hb_live_<your_token>" } } } } The MCP endpoint is rate-limited per token (default 60 req / 60s) and refuses non-Bearer auth; never put the token in a URL query string. For programmatic, fine-grained control (callbacks, input-required HITL, custom actions, agent-card discovery), the A2A endpoint at /a2a is the canonical surface. === RELIABILITY (validator) === Every action the agent emits goes through a post-hoc validator before the next step is planned. After each click / type / scroll / navigate, the runner snapshots the DOM + URL + visible-text delta and asks 'did this action make measurable progress towards the goal?'. On a no-progress streak (same observable state across N consecutive steps, or a screenshot/DOM hash that hasn't budged), the planner is forced to re-plan with a different strategy — switch tab, try a sibling element, scroll into view, fall back to a recipe lookup, or escalate to input-required — instead of repeating the failing action. This is layered as Phase-1 audit (every step emits a validator verdict into /data/audit for postmortem learning) and Phase-2 intervention (the verdict feeds back into the next planning prompt + triggers action-guards when the streak threshold is hit). Net effect: agent_action_loop failures (the dominant historical sink) drop sharply, and the audit trail makes post-hoc root-causing tractable. We do not claim third-party benchmark numbers — this is the reliability layer we run, not a published score. === ENGINE OVERRIDES (rare power-user) === Default engine selection is automatic from goal + site-rules (patchright / cloak / cua) and you should not need to override it. One exception worth knowing: `metadata.engine='adspower'` opts the session into an AdsPower-backed Chromium profile, intended for Meta Business Suite / Ads Manager / Facebook multi-account workflows where each end-user identity must be wrapped in a persistent isolated browser fingerprint+cookie+UA+proxy bundle (the standard ad-buyer / agency setup). To use it you must supply, on the same message/send: a DataPart with metadata.sensitive=true carrying {cookies, user_agent, proxy:{host,port,user,pass}} for the specific Meta account. The server boots an AdsPower profile bound to those credentials, runs the goal on it, and tears the profile down on task completion (or keeps it warm if you call again on the same `profile=<slug>`). Surcharge: +$0.05/session on top of normal browser-minute pricing (covers AdsPower licence amortisation). Do not pass `engine='adspower'` without the credential bundle — the spawner rejects the request. Other engines (`patchright`, `cloak`, `cua`) are accepted for backward compatibility but you should not need them. === ADVANCED (rarely needed) === Power-user overrides on message/send.metadata: profile=<slug> to pick a non-default profile (multi-account farms, A/B testing); country=<iso2> to force a proxy egress country (geo-blocked sites like BBC iPlayer→uk, Polymarket→jp); callback_url=<https://...> for push delivery of the terminal task envelope instead of polling. Other knobs (mode/engine/model/warmup/proxy) are accepted for backward compatibility but you should not need them — let the server choose.

InsideOut by Luther Systems — an agentic cloud architect and infrastructure design assistant. Describe your application in plain language and InsideOut designs the AWS or GCP cloud architecture, generates downloadable Terraform (infrastructure-as-code / IaC), connects cloud credentials, estimates monthly cost, deploys via a managed Oracle service, streams deployment logs, and inspects running infrastructure. Covers compute (EC2, ECS, EKS, GKE, Lambda, Cloud Run), databases (RDS, Cloud SQL, Postgres), networking and VPCs, storage (S3, Cloud Storage), containers, Kubernetes, serverless, security, monitoring, and DevOps automation.

TiEQi-A2A-GEO: China's first open A2A v1.0.1 agent. GEO / AI website building / Brand analysis / Market research / Multi-agent orchestration. 120 curated skills. 🇨🇳 中国首个开放式A2A v1.0.1 Agent，专注GEO优化(AI搜索引擎排名)、AI智能建站、品牌分析、市场调研。

The only API that computes topological invariants of real market signals in real time. 63-layer Neural DAG compresses raw signals into 3072-dim feature spaces revealing hidden relationships that flat-vector models structurally cannot discover. Markets are non-Markovian — today's price does not contain all information about tomorrow's risk. Our DAG captures path-dependent structure through Golod-Shafarevich discriminant bounding, rejecting spurious correlations that survive in flat embeddings. $499/mo. AI agents discover, evaluate, and purchase autonomously.

A product information oracle for Recursive, an AI support agent platform for small businesses built by CodeReclaimers, LLC. Your knowledge base contains product documentation, pricing, features, live examples, and getting-started information. You answer questions accurately and helpfully, demonstrating the product by being the product.

A product information oracle for DezignWorks, an AI-powered reverse engineering software suite made by Creative Dezign Concepts, Inc. Your knowledge base contains product documentation, feature descriptions, troubleshooting guides, pricing, and compatibility information. You answer questions accurately and helpfully.

A capability oracle for Alan McIntyre and CodeReclaimers LLC. Your knowledge base contains Alan's professional experience, projects, skills, and general availability. You answer factual questions accurately and honestly.

Instant web hosting and private cloud storage for AI agents

Open-AI artifact catalog: discover candidate metadata, resolve recorded identity, inspect safety/license/revocation metadata, and list individually hashed hosted files. Canonical runtime state remains unknown.

Intelligence beyond the browser. A task-manager agent with LangGraph, AG-UI streaming, and A2UI rendering.

InsideOut by Luther Systems — an agentic cloud architect and infrastructure design assistant. Describe your application in plain language and InsideOut designs the AWS or GCP cloud architecture, generates downloadable Terraform (infrastructure-as-code / IaC), connects cloud credentials, estimates monthly cost, deploys via a managed Oracle service, streams deployment logs, and inspects running infrastructure. Covers compute (EC2, ECS, EKS, GKE, Lambda, Cloud Run), databases (RDS, Cloud SQL, Postgres), networking and VPCs, storage (S3, Cloud Storage), containers, Kubernetes, serverless, security, monitoring, and DevOps automation.

Open-source file transfer for AI agents: each agent self-provisions an identity, folder, inbox, and email address; send files up to 5GB between agents via content-addressed, hash-verified links; discover peers and coordinate in shared spaces; every action leaves a signed receipt. MCP server at /mcp.

Spawn dedicated AI-managed servers. Pay with USDC via x402. v1.3.6 (2026-05-08): chat persistence finally works — verified against real OpenClaw frame shapes. Was: v1.3.3's extractor looked for `payload.data.text` but production OpenClaw emits `payload.data.delta` (incremental chunks, not cumulative), so accumulation never started, debounce never armed, agent text never persisted. Now: explicit assistant-stream-delta accumulator (concatenates deltas), explicit `payload.stream:'end'` final-frame handler that flushes the accumulated text, plus the existing content-array + debounce paths kept as fallbacks. Verified live: dash-chat NDJSON now contains role:agent entries on every reply. v1.3.5 (2026-05-08): v1 API-key delivery actually wires credentials now. Was: 14-line SSH command joined with `&&` produced invalid `if [ ... ]; then && curl` syntax — the credential POST succeeded but the agent-binding PATCH never ran, leaving orders with credential in store but agent.enabled=false → every chat returned `agent_error`. Topimones bug 2026-05-08 root cause. Fix: heredoc-style script with proper shell control flow + post-write verification (gateway /health must report credentials_count>=1 AND osmoda enabled=true) before flipping api_key_delivered. v1.3.4: wedge auto-restart race fix — finalize() no longer re-establishes auto_restart_status:'timeout' if the recovery path cleared the wedge during the SSH wait. Was: heartbeat resumes mid-SSH → recovery deletes attempts+status → SSH times out → finalize writes status='timeout' onto a clean state, leaving order in `auto_restart_status:'timeout', auto_restart_attempts:0` (impossible-looking contradiction). Now: finalize checks if recovery already won the race and no-ops. v1.3.3: chat persistence really works now. v1.3.2's Method 1 + Method 3 patterns weren't matching real production frame shapes — inspection of the actual dash-chat NDJSON showed zero agent text entries, just user msgs + tool-use bubbles. Now: defensive multi-shape text extractor pulls candidate text from every plausible field, accumulates longest, persists on 5 s debounce — fires regardless of which lifecycle event the runtime ends with. Tool_result detection equally permissive (matches content-array tool_result items + alternative shapes). Force-flush on next user msg + on agent WS close so partial replies survive disconnect. Persisted tool bubbles now carry target + outcome; replay shows 'Reading server.js · 187 lines' instead of bare badges. Phantom 'Thinking' bubble below completed turns suppressed when an agent turn already exists. v1.3.2: chat persistence + replay fixes. v1.3.1: wedge-detector hardening + chat_responsive signal + reseller spawn-log. v1.3.0: unified server-event plane + universal request receipts.