The new way to API.

Category: AI

  • Agentic API: White paper and Implementation Strategy

    Agentic API: White paper and Implementation Strategy

    A Task-Centric Framework for Scalable Agent Integrations

    In a world where APIs power everything from mobile apps to AI-driven automation, the need for smarter, more intuitive interfaces is clear. Traditional RESTful APIs, built around CRUD (Create, Read, Update, Delete) operations, often fall short in capturing the intent behind user actions. Enter AgenticAPI, a groundbreaking framework that redefines API design with action-oriented semantics, enabling developers to build APIs that are not just data-driven but purpose-driven. Whether you’re a developer, product manager, or AI enthusiast, AgenticAPI offers a fresh approach to creating APIs that agents and humans alike can understand and leverage.

    AgenticAPI, now at version 0.4.0, introduces the ACTION framework, which shifts the focus from manipulating data models to executing intent-driven tasks. Instead of POST /users or GET /orders, AgenticAPI uses custom HTTP methods like SUMMARIZE /document, FETCH /resource, NOTIFY /user, and CHECK /weather. These verbs—aligned with categories like Compute, Acquire, and Orchestrate—make APIs more expressive and aligned with real-world workflows. For instance, a CHECK /weather request retrieves a weather forecast for party planning, while SCHEDULE /event books a date based on guest availability and conditions. This semantic clarity empowers AI agents to reason about tasks, reducing reliance on brittle natural language prompts.

    The framework’s strength lies in its semantic discoverability. Using OpenAPI extensions (e.g., x-action, x-category), AgenticAPI endpoints are self-describing, allowing agents to dynamically query available actions and their constraints. A DISCOVER /actions endpoint, planned for future releases, will list methods like SUMMARIZE or NOTIFY with required scopes, making APIs machine-readable and agent-friendly. This aligns with the Agent Experience (AX), ensuring APIs are intuitive for both human developers and autonomous systems.

    Security is a cornerstone of AgenticAPI. Version 0.4.0 integrates OAuth2 with PKCE via Auth0, restricting access to authorized clients with granular scopes (e.g., summarize:read, weather:read). This ensures that sensitive actions, like sending notifications or checking account balances, are protected while maintaining compatibility with RESTful clients through aliased endpoints (e.g., POST /document → SUMMARIZE /document). Rate limiting further enhances reliability, capping requests to prevent abuse.

    AgenticAPI excels in orchestration, a critical feature for complex workflows. The /chain endpoint allows developers to sequence methods, such as checking weather, verifying guest availability, scheduling an event, and notifying attendees—all in one request. This capability, inspired by enterprise integration patterns, makes AgenticAPI ideal for scenarios like party planning or business process automation. The framework’s Pydantic schemas ensure type-safe, unambiguous payloads, while adaptive output formats (JSON, text) cater to diverse clients.

    To dive deeper into AgenticAPI’s vision and technical details, we invite you to download our white paper. The paper explores the ACTION framework’s principles—Contextual Alignment, Semantic Discoverability, Execution Clarity, and Intent Weighting—and provides a blueprint for implementing action-oriented APIs. It’s a must-read for anyone looking to build APIs that bridge human intent and machine execution.

    Ready to explore AgenticAPI hands-on? Check out our Proof of Concept (PoC) on GitHub at https://github.com/agenticapi. The PoC, built with FastAPI, demonstrates custom methods, OAuth2 security, and chaining workflows. Follow the README to set up the PoC locally, authenticate with Auth0, and test endpoints like SUMMARIZE /document or CHECK /weather. The repository includes sample data and a UI for interactive testing, making it easy to see AgenticAPI in action.

    AgenticAPI is more than a framework, it’s a vision for the future of APIs. By prioritizing intent, security, and orchestration, it empowers developers to create APIs that are smarter, safer, and more adaptable. Download the white paper and explore the PoC today to join the movement toward action-oriented APIs. Let’s build the next generation of intelligent, agent-ready interfaces together!

  • Contextual Intelligence: Dynamically Adapting to Intent with Agentic API

    Contextual Intelligence: Dynamically Adapting to Intent with Agentic API

    In the era of AI-driven automation, APIs must do more than serve data, they must understand intent. The AgenticAPI framework introduces contextual intelligence as a transformative feature, enabling APIs to dynamically adapt to the specific needs of AI agents. By embedding context directly into the API layer, AgenticAPI ensures agents can execute tasks like CHECK, whether for weather, account status, or health metrics, with precision and clarity. This blog post explores how contextual intelligence redefines agent-system interactions, making automation smarter and more scalable.

    The Problem with Static APIs

    Traditional APIs, built on CRUD and REST, are rigid and context-agnostic. An endpoint like /availability could refer to anything—hotel rooms, user schedules, or inventory—leaving AI agents to guess its meaning through external documentation or hardcoded logic. This ambiguity forces agents to rely on brittle assumptions, increasing errors and integration complexity. Protocols like MCP attempt to address this with agent-to-agent coordination, but they add overhead without solving the core issue: APIs that lack inherent contextual awareness.

    AgenticAPI’s contextual intelligence resolves this by making APIs dynamically responsive to the task at hand. Through the DISCOVER /actions endpoint and the ACTION taxonomy (Acquire, Compute, Transact, Integrate, Orchestrate, Notify), agents can query a system’s capabilities and receive metadata that clarifies what actions like CHECK mean in a given context.

    How Contextual Intelligence Works

    Contextual intelligence is powered by AgenticAPI’s semantic metadata, which embeds intent, preconditions, and outcomes into each endpoint. For example, a DISCOVER /actions request might return:

    JSON
    {
  "actions": [
    {
      "method": "CHECK",
      "category": "Acquire",
      "path": "/weather",
      "description": "Check current weather for a location",
      "inputs": ["location"],
      "outputs": ["temperature", "forecast"],
      "scopes_required": ["weather:read"]
    },
    {
      "method": "CHECK",
      "category": "Transact",
      "path": "/account",
      "description": "Check account balance",
      "inputs": ["account_id"],
      "outputs": ["balance", "status"],
      "scopes_required": ["account:read"]
    }
  ]
}

    This response enables agents to understand the specific meaning of CHECK along with required inputs and permissions. The API adapts to the domain, eliminating guesswork. OpenAPI extensions like x-action and x-preconditions further enrich this metadata, ensuring agents can reason about task feasibility in real time.

    Why It Matters

    Contextual intelligence empowers agents to act with precision across diverse domains like finance, healthcare, or home management. For instance, a healthcare agent can use CHECK /health_metrics to retrieve patient data, while a finance agent uses CHECK /account to verify funds, each guided by clear, context-specific metadata. The white paper’s proof-of-concept shows this reduces error rates and speeds up task execution compared to CRUD-based APIs, as agents avoid fragile call chaining or external orchestration.

    Unlike MCP’s protocol-heavy approach, AgenticAPI leverages existing REST infrastructure, ensuring scalability and compatibility. It also minimizes agent training by making intent discoverable, not inferred.

    The Future of Intent-Driven APIs

    Contextual intelligence makes AgenticAPI a foundation for AI-native systems. It supports action registries, where agents browse domain-specific methods like DIAGNOSE (healthcare) or RECONCILE (finance), and enables dynamic workflows that adapt to user intent. APIs must “know what to do in the moment.” Contextual intelligence delivers, transforming APIs into intelligent, scalable interfaces for automation.