Agents

An index and topic collection covering AI agents, agent frameworks, and agent runtimes that enable autonomous reasoning, tool use, and multi-step task execution. This profile catalogs the platforms and open-source projects that let developers build, orchestrate, and deploy LLM-powered agents, including foundational frameworks like LangChain, LangGraph, CrewAI, AutoGen, and AutoGPT, hosted agent platforms like Lindy, Relevance AI, and Composio, and provider-native agent runtimes from OpenAI, Anthropic, Google, and Microsoft. Distinct from foundation models and from Agent Skills (capability packages), the Agents topic focuses on the orchestration layer where planning, memory, tool calling, and execution come together.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.

How we profile Agents

Each block below is one kind of artifact we hold for Agents. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

Features 8

The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.

Notable capabilities this provider offers.

Planning and Reasoning Loops

Agent frameworks like LangGraph, AutoGen, and CrewAI provide structured loops for planning, reflection, and multi-step reasoning over user goals, breaking complex tasks into ord...

Tool Calling and Function Use

Agents invoke external functions, APIs, and aggregated tool catalogs through provider-native tool calling, expanding their reach beyond text generation into real-world action.

Memory and State Management

Frameworks like Letta and LangGraph provide persistent memory, conversation state, and long-running execution context so agents can resume work, remember users, and accumulate k...

Multi-Agent Orchestration

CrewAI, AutoGen, and LangGraph enable multiple specialized agents to collaborate, delegate sub-tasks, and reach consensus, modeling teams of role-based workers around a shared g...

Provider-Native Agent Runtimes

OpenAI Assistants, Anthropic Claude tool use, Google ADK, Amazon Bedrock Agents, and Microsoft Azure AI Foundry expose first-party agent runtimes that handle planning, tool invo...

Browser and Web Agents

Agents like AgentQL and browser-driving frameworks let LLMs navigate real web pages, fill forms, and extract structured data, extending agent reach to systems that lack APIs.

Observability and Evaluation

Platforms like Portkey, TrueFoundry, and Bifrost provide tracing, evaluation, cost tracking, and gateway routing across agent runs to make agent behavior observable and debuggable.

Open Governance and Interoperability

The Linux Foundation Agentic AI Foundation and projects like kagent and AgentGateway are establishing open standards for agent-to-agent communication, identity, and runtime port...

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Semantic Vocabularies 1

JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.

JSON-LD contexts and semantic vocabularies used across these APIs.

Agents Context

8 classes · 20 properties

JSON-LD

JSON Schema 2

Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.

Standalone JSON Schema definitions for this provider's data models.

AgentDefinition

10 properties

JSON SCHEMA

AgentRun

11 properties

JSON SCHEMA

JSON Structure 2

JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.

JSON Structure definitions describing this provider's data shapes.

Agents Agent Definition Structure

10 properties

JSON STRUCTURE

Agents Agent Run Structure

11 properties

JSON STRUCTURE

Examples 2

Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.

Example request and response payloads for these APIs.

Agents Agent Definition Example

10 fields

EXAMPLE

Agents Agent Run Example

11 fields

EXAMPLE

Use Cases 7

What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.

What developers build with this provider.

Customer Support Automation

Hosted agent platforms like Lindy, Relevance AI, and Microsoft Power Virtual Agents handle inbound support tickets, route conversations, and resolve common requests end-to-end.

Research and Knowledge Work

LangChain and LlamaIndex agents combine retrieval over enterprise documents with reasoning to answer complex questions and synthesize multi-source briefings.

Sales and Outbound Workflows

Agents built on Lindy, Relevance AI, and Composio prospect leads, draft outreach, log CRM activity, and orchestrate multi-step sales sequences.

Software Engineering Agents

AutoGPT, AutoGen, and CrewAI-based engineering agents read repositories, draft pull requests, run tests, and iterate on code under human review.

Voice and Telephony Agents

LiveKit and similar runtimes power real-time voice agents that handle phone calls, meetings, and live conversations using streaming LLMs and tool calling.

Internal Operations and IT Automation

Agentic platforms like Restack, Trigger.dev, and Stackmint orchestrate long-running internal workflows across SaaS, databases, and identity systems.

Multi-Agent Team Simulations

CrewAI and AutoGen model role-based teams (researcher, writer, reviewer) collaborating on a single deliverable, producing higher-quality output than a single agent.

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Integrations 8

Pre-built integrations with other platforms tell you where this provider already fits in a stack.

Pre-built integrations with other platforms and tools.

LangChain

The most widely used open-source framework for building LLM applications, including chains, agents, retrieval, memory, and tool calling across dozens of providers.

LangGraph

A graph-based runtime from LangChain for stateful, multi-actor, long-running agent workflows with checkpointing and human-in-the-loop.

CrewAI

Multi-agent framework for orchestrating role-based agent crews that collaborate on complex tasks.

AutoGen

Microsoft's open-source framework for building multi-agent conversations with planner, executor, and critic roles.

Composio

Agent execution platform exposing 1000+ apps as governed tools for any agent framework or model.

Letta

Stateful agent platform (formerly MemGPT) focused on long-term memory and persistent agent identity.

OpenAI Assistants

OpenAI's hosted agent runtime with built-in tool use, retrieval, code interpreter, and threads.

Amazon Bedrock Agents

AWS's managed agent runtime over foundation models with action groups, knowledge bases, and guardrails.

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Resources

Every other property we hold for Agents — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

← All providers · Data indexed from github.com/api-evangelist/agents · machine-readable index on apis.io