Agno
What is Agno?
TL;DRAgno (formerly Phidata) is a lightweight Python framework designed to build high-performance, multimodal AI agents and multi-agent teams. It offers developers a fast and structured foundation to deploy intelligent systems equipped with memory, knowledge bases, and structured tool access.
- Lightweight Python agent framework optimized for speed and memory efficiency
- Support for multi-agent teams with task delegation and shared context
- Built-in vector database connectors and persistent agent memory
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About
Agno (formerly Phidata) is a lightweight Python framework designed to build high-performance, multimodal AI agents and multi-agent teams. It offers developers a fast and structured foundation to deploy intelligent systems equipped with memory, knowledge bases, and structured tool access.
Developers and engineering teams use Agno to construct autonomous workflows, such as financial analysis agents, customer support teams, and research pipelines. By coordinating specialized sub-agents with clear task delegation, Agno handles complex reasoning workflows that require external tools, vector search, and persistent state across user sessions.
Agno differentiates itself through its lightweight architecture and focus on low latency. Unlike bloated agent libraries, Agno minimizes framework overhead while offering an optional cloud UI for tracking agent runs, monitoring API calls, and evaluating outputs. The core library is open-source, while Agno Cloud offers team management and observability features.
For FutureStack, Agno belongs in AI Agents because it provides specialized tools for multi-agent orchestration and autonomous systems. It is best for AI engineers, software architects, and product teams building multi-agent backend applications.
Use Cases
Model Quality & Safety Monitoring
Copy promptCopy prompt for coding agentCContosoHomeChatSessionsTracesStudioLearningMemoryKnowledgeMetricsEvaluationApprovalsSchedulerManage OSSettingsTry Live Demo.
Automated Lead Data Enrichment
GPT-5.6-SolSales AgentFinds qualified prospects and drafts personalized outbound.
Multi-agent Task Delegation
Support for multi-agent teams with task delegation and shared context.
Contextual Knowledge Retrieval
Built-in vector database connectors and persistent agent memory.
Key Features
- Lightweight Python agent framework optimized for speed and memory efficiency
- Support for multi-agent teams with task delegation and shared context
- Built-in vector database connectors and persistent agent memory
- Cloud platform for agent monitoring, telemetry, and execution logs
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Pricing summary
Agno offers a free open-source framework alongside paid cloud tiers starting at $20/month for advanced monitoring, telemetry, and team collaboration.
Pricing & Plans
Community
Open-source framework for building local agents.
Free
- Open-source framework
- Unlimited local agents
- Basic memory integration
- Community support
Popular
Pro
Cloud platform for agent monitoring and telemetry.
$20/month
- Cloud monitoring dashboard
- Advanced agent telemetry
- Team collaboration
- Priority execution
Enterprise
Dedicated cloud infrastructure and security controls.
$100/month
- Custom deployment
- SLA guarantees
- Dedicated support
- Advanced security controls
Other pricing notes
- Pricing checked on 2026-07-31 from the official Agno website.
- The core Python agent framework is free to use locally.
- Cloud platform tiers charge for hosted monitoring, analytics, and team seats.
Pricing last checked: July 2026Official pricing
Pros & Cons
Pros
- High execution speed compared to heavier agent frameworks
- Clean API design for defining specialized multi-agent teams
- Supports multimodal inputs including image, audio, and video
- Offers both open-source library and cloud management tools
- Built-in memory and state management for persistent sessions
Cons
- Advanced enterprise monitoring features require paid cloud plans
- Developer effort required to tune prompt prompts and agent handoffs
- API changes can occur as the framework expands functionality
- Token costs rise when running complex multi-agent conversations
- Requires Python proficiency for custom agent pipeline development
Frequently Asked Questions
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