# themanojdesai/python-a2a

Python A2A is a powerful, easy-to-use library for implementing Google's [Agent-to-Agent (A2A) protocol](https://google.github.io/A2A/). It enables seamless communication between AI agents, creating interoperable agent ecosystems that can collaborate to solve complex problems.

Repository: https://github.com/themanojdesai/python-a2a
Canonical: https://ross.abutalabs.com/products/python-a2a
Language: Python
License: MIT
License Family: permissive
Last push: 2025-09-06T08:10:09+00:00

## Health v2 (maintenance only)
Score: 37/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 40, release rhythm 35, longevity 36
- inputs: {"age_days": 511, "days_push": 361, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1008, forks 143 (observed 2026-08-28T04:03:12.722457+00:00)

## What it is
Python A2A is a Python library implementing Google's Agent-to-Agent (A2A) protocol with Model Context Protocol (MCP) integration. It enables AI agents to communicate and collaborate across different implementations through a standardized JSON-RPC 2.0-based protocol.

## Use cases
- build interoperable AI agent ecosystems
- implement Google's A2A protocol in Python
- connect AI agents to external tools via MCP
- create multi-agent systems that collaborate on complex tasks
- expose an LLM-powered agent as an A2A-compatible server
- integrate OpenAI, Anthropic, or AWS Bedrock models into agent workflows

## When to choose
- you need agents from different frameworks or vendors to talk to each other
- you want a Pythonic, well-documented implementation of the A2A protocol
- you need MCP support for giving agents access to external tools and data
- you're building production multi-agent systems with stdio or SSE transports

## When to avoid
- you only need a single-agent chatbot with no agent-to-agent communication
- you're locked into a framework that already provides native A2A support
- you need a non-Python implementation of the protocol

## Facets
- artifact type: library
- maturity: active
- function: agent-framework, rpc, mcp, llm-inference, api-framework
- domain: large-language-models, apis, developer-tools
- platform: python, cross-platform
- tags: a2a-protocol, agent-to-agent, multi-agent-systems, -rpc, interoperability, google-a2a, ai-agents

## Member repositories
- themanojdesai/python-a2a (main) score 37

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:12.722457+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:12:14.137651+00:00, confidence not recorded.
  - readme: https://github.com/themanojdesai/python-a2a (fetched 2026-08-28T04:03:12.722457+00:00, sha 9ee23a778eaf)
  - registry_pypi: https://pypi.org/pypi/python-a2a/json (fetched 2026-08-29T13:12:38.758530+00:00, sha f9de15e16a38)
- Data as of 2026-08-30T08:39:29.467469+00:00.