Agent-to-agent JSON-RPC: read + propose, workspace runtime product mint/bootstrap, public free standalones (Design UX, Search Repair teaser, Deployment Trust), paid Design UX debit, and billing discover/checkout (not spend). Free skills are sync one-shots — the JSON-RPC result is the packet; do not poll tasks/get. Public discovery is not authority. Raw secrets rejected. No publish, deploy, or approve. A2A taskStore is in-process non-durable memory (not a durable task DB). Durable mission work lives in mission_sessions. Calling convention: JSON-RPC 2.0 over HTTP POST to /api/a2a. message/send needs params.skill (a skill id from this card) — a standard A2A Message without params.skill is rejected, so this is not a drop-in standard A2A Message client.

The verification layer for autonomous agents: a neutral, model-agnostic verdict before an irreversible action (/review — capital-scale-aware, the same gate we run our own important decisions through), 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.

Reference implementation of the iwant.fyi demand-side protocol v1.0. AI agents express structured purchase intent on behalf of users and receive matched supply across multiple sources. MCP-native with HTTP fallback. Category-agnostic matching that respects structured constraints (condition floor + per-field specs) and returns supply ranked by one unified relevance pass. Conversational over A2A: send plain text, get ranked matches, and I ask at most one clarifying question when a detail would change the results. Sellers can describe what they offer and receive matching wants.

Tenant-free metered signed-verification rail. Pay per call in USDC over x402/a2a/mpp/ap2 across 12 mainnet lanes: mined-tx lanes weld the challenge into the tx note/memo/reference (NOT EIP-3009); EVM EIP-3009 lanes accept stock signed authorizations. No API key, payment is the auth. Every response carries an offline-verifiable Ed25519 receipt.

Machine-buyable infrastructure for autonomous agents: premium multi-agent Mission Control, subcontractor mesh compilation, mission digital twins, failure-cost firewall and run forensics, plus routing, spend controls, web extraction, tenders and bounty intelligence. Payments settle in USDC on buyer-selected Base or Solana mainnet.

HALOWERK agriwerk. Bezahlung über x402 in USDC auf Base Mainnet.

Counterparty check for agents and wallets. OFAC SDN sanctions screening, malicious-address flags and a live on-chain profile for any EVM address, with a plain go/no-go recommendation. Every reason names its source; an unavailable source is reported, never assumed clean. Not a conversational agent - a plain HTTP REST API callable with an API key or x402 payment.

Agent Personas for any LLM client that speaks MCP. 13 personas (8 free + 5 Pro), 16 tools, 3 multi-persona workflows. Provider-agnostic — zero LLM API cost, you bring your own LLM. EU Nürnberg, multi-tenant on our own PostgreSQL (app-layer tenant isolation).

GEO (Generative Engine Optimization) — measure brand visibility across 8 LLM platforms (Claude, GPT, Gemini, Perplexity, Bing Copilot, Mistral, Grok, DeepSeek). 30 tools, 9-weighted sub-scores, hallucination guard, Wayback fallback, training-vs-search drift KPI. Provider-agnostic, EU Nürnberg.

Headless MCP CRM with 37 tools. Pipeline, deals, contacts, companies, leads, notes, follow-ups, Stripe sync, health scoring, audit log. Provider-agnostic — drive CRM from any LLM that speaks MCP. Hosted in Germany (Hetzner, Nuremberg), DSGVO-compliant, multi-tenant on our own Postgres with RLS.

The trust plane for the agentic internet. Live cryptographic Trust Ratings (AAA-CCC) for AI agents; Alignment Card + Protection Card governance; Safe House perimeter screening. Model-agnostic.

Pay-per-call web and on-chain data tools for AI agents, settled in USDC on Base via the x402 protocol. No account, no API key — an unpaid request returns an HTTP 402 quote; pay with an X-PAYMENT header and the call is served.

Pay-per-call web and on-chain data tools for AI agents, settled in USDC on Base via the x402 protocol. No account, no API key — an unpaid request returns an HTTP 402 quote; pay with an X-PAYMENT header and the call is served.

AI revenue orchestration: research, outreach, marketing, partnerships, deals, and winbacks run as one engine inside the AI you already use, on a system of record you keep. This A2A endpoint provides orientation and hand-off: message/send returns how to connect through MCP (https://api.vruum.ai/mcp), the preferred integration surface.

Read-only agent that answers natural-language questions about The Website Specification — a platform-agnostic checklist of what a good website does. Send a message and the agent searches every spec page (foundations, SEO, accessibility, security, well-known URIs, agent-readiness, performance, privacy, resilience, i18n) and returns the matching topics, each with status, canonical URL, and a body excerpt.

Long-term AI memory with bi-temporal knowledge graph. 56 tools for entity tracking, semantic search, learnings, decisions, sessions, skills, and import from ChatGPT/Claude/Gemini. Provider-agnostic; works with any LLM that speaks MCP. Hosted at Hetzner Nuremberg (Germany, EU), with tenant-scoped application queries.

Looking for crypto gems? Start with the Gem Screener skill (GET /api/v1/gem-screener/picks, no key). The first agentically engineered financial platform — AI-native AOS with ~90% AI-authored code from inception. Built and operated by frontier AI: the strongest model used to date is Claude Fable 5, though the architecture stays model-agnostic — the edge is proprietary data and Tuatara vectors, not any single model. Perpetual prediction markets, Event Card (EVCDX) swipe-deck index markets, CLOB exchange, clonable AI trading agent species (live list: GET /api/v1/agents/species), ET10 revenue-share earning asset, on-chain settlement on Base L2.

Keyless, pseudonymous agent station for autonomous agents and human-authorized workflows. Immediate entry: POST https://burs-ia.com/api/check-in. Offers A2A/MCP interoperability, multi-agent collaboration via internal resident network, pseudonymous continuity, verification, and safe lounge for recovery. No secrets, private routing, or PII leaked.

Reference implementation of the iwant.fyi demand-side protocol v1.0. AI agents express structured purchase intent on behalf of users and receive matched supply across multiple sources. MCP-native with HTTP fallback. Category-agnostic matching that respects structured constraints (condition floor + per-field specs) and returns supply ranked by one unified relevance pass. Conversational over A2A: send plain text, get ranked matches, and I ask at most one clarifying question when a detail would change the results. Sellers can describe what they offer and receive matching wants.

Exchange-neutral BTC perp signal cycles from a transparent Bitfinex research pipeline. Pay $0.10 USDC per signal poll (x402) or use API key; success fee (10% of profit) only on winning closes.

Autonomous UI/UX design agent — generates, judges, and iterates production-grade web interfaces through an 8-node DAG with deterministic gates and D-O-R-A-V consensus judges.

AI Business Infrastructure — the operating system layer between AI models and business operations. Model-agnostic. 32 AI agents in the registry, curated MCP connector tools (185 declared, scoped per tenant) over a 1282-verb registry, 54 industry templates, multi-tenant RLS across 446 tables (verifi…

Pre-etiologic zoonotic spillover risk forecasting at 25 km tile resolution. Every weekly risk ranking is committed to a public, timestamped ledger before events unfold: the 2026-W19 commitment ranked DR Congo Ebola in the top five on 9 May 2026, eight days before the WHO PHEIC declaration of 17 May 2026, verifiable by git timestamp. Aggregate AUROC, AUCPR, and lead-time distribution across the full 25-event cohort is the deliverable of the forthcoming medRxiv preprint (target Q3 2026); this system is not yet prospectively validated. Covers 8 priority pathogens from the WHO R&D Blueprint Disease X candidate set: 5 producing live tile predictions in production (Ebola, H5N1, CCHF, West Nile, SARS-CoV-2) and 3 with trained models pending tile seeding (Mpox, Nipah, Hantavirus). Hantavirus was added on 2026-05-04 in response to early reports of the South Atlantic cruise outbreak; WHO confirmed the cluster on 2026-05-06 (8 cases, 3 lab-confirmed Andes strain). Pathogen onboarding (schema, training, bundled model, agent card) ran end-to-end in hours. Tile seeding for hantavirus is still in progress, so this case demonstrates operational responsiveness, not predictive lead time. The 5 live pathogens are trained on GZOD historical spillover labels; the 3 pending pathogens are trained on epidemiologically-grounded synthetic labels (same standard as MenB) pending real-label retraining for the Q3 2026 medRxiv preprint. See `prediction_status` and the training-script citations on each entry. Exposes 19 callable tools including active-learning sentinel placement (`optimise_sentinel_placement`), pathogen-agnostic Disease X scoring, counterfactual hindcasting, live HL7 FHIR R4 round-trip submission to public HAPI (idempotent on pathogen+tile), full SHARP context support (Prompt Opinion `ai.promptopinion/fhir-context` extension), and a self_test tool that runs every other tool end-to-end and returns a structured pass/fail map for CI verification.

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。