Phidata — AI Agent Framework: Live Stats & TrendScore

Phidata builds AI agents with memory, knowledge, and reasoning tools. We track how its approach compares to CrewAI and LangGraph for production agentic applications.

GitHub data synced: Jun 19, 2026 • Sentiment updated: Jun 23, 2026

GitHub Statistics

Community Sentiment

Community Buzz: I received following comment on my hallucinations blog post, 'Why does AI forget what you said (and how to fix it)' from Dev.to. Another user on GitHub mentioned 'Certify agent framework compatibility for OpenAI-compatible clients' for Phidata.

Pros & Cons

What People Love

Modular framework design, Phidata's compatibility with OpenAI

Common Complaints

Memory poisoning attacks, Data leakage

Biggest Positive: Modular Framework

Biggest Negative: Memory Poisoning

Why Phidata Stands Out

Phidata is valuable because it takes a unique approach to agentic software development. By integrating 100+ APIs and background execution, Phidata enables developers to build complex systems that can learn and adapt in real-time. Additionally, Phidata's stateless, horizontally scalable runtime ensures high performance and per-user and per-session isolation ensures secure data handling. This makes Phidata an ideal choice for developers looking to build complex, multi-agent systems.

Built With

Build a personal research assistant that reads 50 papers and writes a literature review — Phidata chains search, extraction, and synthesis agents automatically, Build a self-learning data agent that grounds in six layers of context — Phidata integrates 50+ APIs and background execution, Build a multi-agent investment committee that debates and allocates capital — Phidata enables runtime approval enforcement and native tracing, Build a post-IDE coding agent that improves over time — Phidata enables per-user and per-session isolation, Build a personal agent that learns your preferences — Phidata integrates guardrails and evaluations into the agent loop

Getting Started

  1. pip install uvx
  2. export ANTHROPIC_API_KEY='***'
  3. uvx --python 3.12 --with 'agno[os]' --with anthropic --with mcp fastapi dev agno_assist.py
  4. Open [os.agno.com](https://os.agno.com) and sign in
  5. Click 'Add new OS' in the top navigation
  6. Enter your endpoint URL (default: http://localhost:8000)

About

Build, run, and manage agent platforms.

Official site: https://docs.agno.com

Category & Tags

Category: data

Tags: agents, ai, ai-agents, developer-tools, python

Market Context

Phidata is positioned among other agent frameworks like LangGraph, CrewAI, and AutoGen, with a focus on modular design and security.