Agent runtimes: Agno & Mastra

The first wave of agent frameworks — LangChain, LangGraph, AutoGen, CrewAI — are orchestration libraries: powerful, but you assemble the pieces (model client, memory store, tool layer, RAG, evals) yourself. A newer class, agent runtimes, takes a different stance: ship the whole production stack as one batteries-included package, optimized for speed and tightly integrated with a single language ecosystem. Two lead it — Agno for Python, Mastra for TypeScript.

What a runtime bundles

The selling point is that everything you’d otherwise wire together comes in the box, with one consistent API:

Agno — the fast Python runtime

Agno is Python-native and obsessed with performance: agents instantiate in microseconds with a tiny per-agent memory footprint, so you can run many at once. It’s model-agnostic and comes with built-in memory, knowledge (vector RAG), tools, structured output, multi-modal support, and agent teams — define an agent in a few lines and the stack is already there.

# Reference — runs locally with `pip install agno`, not in the browser.
from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.duckduckgo import DuckDuckGoTools

agent = Agent(
    model=Claude(id="claude-sonnet-4-6"),
    tools=[DuckDuckGoTools()],     # tools, memory, knowledge are built in
    markdown=True,
)
agent.print_response("Summarize this week's agent-framework news.")

Mastra — the TypeScript runtime

Mastra brings agents to the JavaScript/TypeScript world — Node, Next.js, serverless — where most web products actually live. It bundles agents, deterministic graph workflows, RAG, evals, memory, and observability, and slots into the web/serverless deploy story (e.g. Vercel). For a full-stack team already in TypeScript, it removes the “now drop into a separate Python service for the agent” friction.

// Reference — part of a TypeScript/Node project, not runnable here.
import { Agent } from "@mastra/core/agent";
import { anthropic } from "@ai-sdk/anthropic";

export const researchAgent = new Agent({
  name: "research-agent",
  instructions: "Research a topic and summarize the findings.",
  model: anthropic("claude-sonnet-4-6"),
  tools: { /* web search, retrieval, ... */ },
});

Choosing one

In one breath

• Agent runtimes ship the whole production stack — model, memory, tools, RAG, workflows, evals, deploy — as one batteries-included package tuned for speed and a language, versus orchestration libraries you assemble yourself.
• Agno is the Python runtime: performance-obsessed (microsecond agent creation, tiny footprint), model-agnostic, with built-in memory/knowledge/tools/teams.
• Mastra is the TypeScript runtime: agents + graph workflows + RAG + evals + memory + observability, native to the JS/Node/Next.js web ecosystem.
• Choose by ecosystem and shape: Python and lightweight speed → Agno; a TypeScript web/serverless product → Mastra.
• The boundary with orchestration libraries is bundling, not capability — and it’s blurring as both sides converge.

Quick check

Next

Agent runtimes are one corner of the framework landscape; compare the conversational AutoGen, the graph-based LangGraph, and the role-based CrewAI, all sitting on the framework-agnostic orchestration patterns.