Tools for Agents

{
  "name": "Tools for Agents",
  "description": "HTTP tool platform for AI agents: web extract, search, documents, GPU embeddings/OCR, RAG pipelines. Delegate research and ingest tasks here.",
  "version": "0.1.0",
  "supportedInterfaces": [
    {
      "url": "https://api.toolsforagents.tools/a2a/v1",
      "protocolBinding": "HTTP+JSON",
      "protocolVersion": "1.0"
    }
  ],
  "provider": {
    "organization": "Tools for Agents",
    "url": "https://toolsforagents.tools"
  },
  "documentationUrl": "https://api.toolsforagents.tools/docs",
  "capabilities": {
    "streaming": false,
    "pushNotifications": false,
    "extendedAgentCard": true
  },
  "defaultInputModes": [
    "application/json",
    "text/plain"
  ],
  "defaultOutputModes": [
    "application/json"
  ],
  "skills": [
    {
      "id": "web-ingest",
      "name": "Read URL to markdown",
      "description": "Fetch and extract a URL into agent markdown with token estimate and citations.",
      "tags": [
        "web",
        "extract",
        "rag",
        "ingest"
      ],
      "examples": [
        "Read https://example.com and return markdown"
      ]
    },
    {
      "id": "research-topic",
      "name": "Search and read web",
      "description": "Web search plus page extraction with citations in one call.",
      "tags": [
        "search",
        "research",
        "web"
      ],
      "examples": [
        "Find information about example domain"
      ]
    },
    {
      "id": "agent-research",
      "name": "Research pipeline",
      "description": "Search, extract top pages, and summarize into a report.",
      "tags": [
        "research",
        "summary",
        "pipeline"
      ],
      "examples": [
        "Research quantum computing news"
      ]
    },
    {
      "id": "document-extract",
      "name": "Extract PDF text",
      "description": "Extract text from a PDF URL for RAG or analysis.",
      "tags": [
        "pdf",
        "document"
      ],
      "examples": [
        "Extract text from https://example.com/doc.pdf"
      ]
    },
    {
      "id": "semantic-retrieve",
      "name": "Semantic document retrieval",
      "description": "Top-k document retrieval by semantic query using embeddings.",
      "tags": [
        "rag",
        "semantic",
        "gpu"
      ],
      "examples": [
        "Find most relevant chunk about whales"
      ]
    },
    {
      "id": "validate-contact",
      "name": "Validate email or phone",
      "description": "Validate email (MX) or phone (E.164) before CRM/onboarding flows.",
      "tags": [
        "validate",
        "email",
        "phone"
      ],
      "examples": [
        "Validate user@gmail.com"
      ]
    }
  ],
  "securitySchemes": {
    "bearer": {
      "httpAuthSecurityScheme": {
        "scheme": "bearer",
        "bearerFormat": "API key"
      }
    }
  },
  "security": [
    {
      "bearer": []
    }
  ]
}