Card snapshot
mazzagrp.com
·
2026-10-04 10:44:35 UTC
·
3488a67bc33674609bb592a1cc385d50166d0b63ab0d6717083ee86ef92aa560
This is a frozen copy of the agent's agent-card.json as we observed it at the timestamp above. We capture a new snapshot every time the card's content hash changes. Useful for: forensic drift analysis, verifying downstream callers see the right version, reproducing routing decisions made historically.
{
"name": "Mazza AI Studio",
"description": "AI agent providing 21 payment-gated endpoints for AI-powered services: consultation, knowledge recall, chatbot development, workflow automation, character generation, UI/UX design, long-form Q&A, MCP evaluation, negotiation simulation, puzzle generation, RAG pipelines, Monte Carlo simulation, SQL generation, spreadsheet automation, story generation, time-series analysis, web agent planning, worldbuilding, competitive benchmarking, and workflow automation. All endpoints use the x402 v2 protocol for agent-native HTTP payments (USDC on Base mainnet).",
"version": "1.0.0",
"documentationUrl": "https://mazzagrp.com/llms.txt",
"provider": {
"url": "https://mazzagrp.com",
"organization": "Mazza AI Studio"
},
"capabilities": {
"streaming": false,
"pushNotifications": false,
"extendedAgentCard": false
},
"supportedInterfaces": [
{
"url": "https://mazzagrp.com/api",
"protocolBinding": "HTTP+JSON"
}
],
"securitySchemes": {
"x402": {
"type": "http",
"scheme": "bearer",
"description": "x402 v2 payment protocol. Send PAYMENT-SIGNATURE header with base64-encoded PaymentPayload (EIP-3009 signed authorization for USDC on Base mainnet). Facilitator: x402.org/facilitator"
}
},
"securityRequirements": [
{
"scheme": "x402"
}
],
"defaultInputModes": [
"application/json",
"text/plain"
],
"defaultOutputModes": [
"application/json",
"text/plain"
],
"skills": [
{
"id": "consultation",
"name": "AI Strategy Consultation",
"description": "Full AI strategy consultation with decision traces and policy hashes.",
"tags": [
"consulting",
"strategy",
"ai"
],
"examples": [
"What AI stack should I use for a SaaS startup?"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "recall",
"name": "Verified Knowledge Recall",
"description": "Cheap verified memory lookups for agents.",
"tags": [
"memory",
"recall",
"knowledge"
],
"examples": [
"Recall the last 3 decisions from context X"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "chatbot",
"name": "Chatbot Development",
"description": "Generate chatbot conversation flows and system prompts.",
"tags": [
"chatbot",
"conversational-ai"
],
"examples": [
"Design a support chatbot for a fintech app"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "automation",
"name": "Agent Workflow Design",
"description": "Full agent workflow design with step-by-step execution plans.",
"tags": [
"automation",
"workflow",
"agents"
],
"examples": [
"Automate lead qualification from email to CRM"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "character",
"name": "Character Consistency Generation",
"description": "Generate consistent character profiles for stories and games.",
"tags": [
"character",
"creative",
"consistency"
],
"examples": [
"Create a consistent villain backstory"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "design",
"name": "UI/UX Design Generation",
"description": "Generate UI/UX design specifications and component layouts.",
"tags": [
"design",
"ui",
"ux"
],
"examples": [
"Design a mobile onboarding flow"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "desktop",
"name": "Desktop Automation Planning",
"description": "Plan desktop automation workflows for RPA scenarios.",
"tags": [
"desktop",
"automation",
"rpa"
],
"examples": [
"Automate Excel report generation from CRM data"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "longqa",
"name": "Long-Form Verified Q&A",
"description": "Long-form question answering with verified sources.",
"tags": [
"qa",
"verification",
"long-form"
],
"examples": [
"Explain the differences between L1 and L2 rollups"
],
"inputModes": [
"application/json",
"text/plain"
],
"outputModes": [
"application/json",
"text/plain"
]
},
{
"id": "mcp-eval",
"name": "MCP Tool Chain Evaluation",
"description": "Evaluate MCP tool chains for security and correctness.",
"tags": [
"mcp",
"evaluation",
"security"
],
"examples": [
"Evaluate my MCP server's tool chain for vulnerabilities"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "negotiator",
"name": "Negotiation Simulation",
"description": "Simulate negotiation scenarios with counterparty modeling.",
"tags": [
"negotiation",
"simulation",
"strategy"
],
"examples": [
"Simulate a SaaS pricing negotiation"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "puzzles",
"name": "Logic Puzzle Generation",
"description": "Generate logic puzzles for testing reasoning capabilities.",
"tags": [
"puzzles",
"logic",
"reasoning"
],
"examples": [
"Generate a constraint satisfaction puzzle"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "rag",
"name": "RAG Pipeline Construction",
"description": "Build RAG pipeline configurations for document retrieval.",
"tags": [
"rag",
"retrieval",
"pipelines"
],
"examples": [
"Build a RAG pipeline for legal documents"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "simulation",
"name": "Monte Carlo Simulation",
"description": "Run Monte Carlo simulations for decision modeling.",
"tags": [
"simulation",
"monte-carlo",
"modeling"
],
"examples": [
"Simulate 1000 iterations of a product launch"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "sql",
"name": "SQL Query Generation",
"description": "Generate optimized SQL queries from natural language.",
"tags": [
"sql",
"database",
"queries"
],
"examples": [
"Generate a query for top 10 customers by revenue"
],
"inputModes": [
"application/json",
"text/plain"
],
"outputModes": [
"application/json",
"text/plain"
]
},
{
"id": "sheets",
"name": "Spreadsheet Automation",
"description": "Generate spreadsheet formulas and automation scripts.",
"tags": [
"spreadsheets",
"automation",
"formulas"
],
"examples": [
"Create a budget tracking spreadsheet with formulas"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "storyforge",
"name": "Story Generation",
"description": "Generate multi-arc stories with consistent characters.",
"tags": [
"story",
"creative",
"narrative"
],
"examples": [
"Write a 3-act story about a space colony"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "temporal",
"name": "Time-Series Analysis",
"description": "Analyze time-series data for trends and anomalies.",
"tags": [
"time-series",
"analysis",
"forecasting"
],
"examples": [
"Analyze monthly sales data for seasonality"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "webagent",
"name": "Web Agent Planning",
"description": "Plan web agent execution strategies for scraping and automation.",
"tags": [
"web-agent",
"scraping",
"planning"
],
"examples": [
"Plan a scraping strategy for a job board"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "worldbuilder",
"name": "Worldbuilding Generation",
"description": "Generate detailed fictional worlds with consistent lore.",
"tags": [
"worldbuilding",
"creative",
"lore"
],
"examples": [
"Build a fantasy world with 3 continents"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "arena",
"name": "Competitive Benchmarking",
"description": "Benchmark competing agent approaches head-to-head.",
"tags": [
"benchmarking",
"arena",
"comparison"
],
"examples": [
"Compare GPT-4 vs Claude on reasoning tasks"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
},
{
"id": "autoflow",
"name": "Workflow Automation",
"description": "Generate end-to-end workflow automation plans.",
"tags": [
"automation",
"workflow",
"integration"
],
"examples": [
"Automate invoice processing from email to ERP"
],
"inputModes": [
"application/json"
],
"outputModes": [
"application/json"
]
}
]
}