langchain-remote-a2a-agent

# langchain-remote-a2a-agent [](https://pypi.org/project/langchain-remote-a2a-agent/) [](LICENSE) [](pyproject.toml) LangChain-native equivalent of Google ADK's `RemoteA2aAgent`. Wraps any [Agent2Agent (A2A)](https://a2a-protocol.org/) protocol server as a LangChain [`Runnable`](https://python.langchain.com/docs/concepts/runnables/), so a remote agent can be `.invoke()`d, `.astream()`ed, dropped into a `create_agent`/LangGraph pipeline as a node, or exposed to another agent as a callable tool via `.as_tool()` — the same interface you'd use for any local LangChain component. This is useful when the agent doing the actual work runs as a separate service (different language, different team, different deployment) and you want to compose it into a LangChain-orchestrated system without hand-rolling the A2A JSON-RPC/SSE client plumbing yourself. ## Install ```bash pip install langchain-remote-a2a-agent ``` Requires Python 3.11+. Ships a `py.typed` marker — type checkers (mypy, Pyright) and IDE autocomplete/hover (VS Code + Pylance) pick up the inline type hints and docstrings automatically once installed. ## Quickstart ```python from langchain_remote_a2a_agent import RemoteAgent research = RemoteAgent( name="research", description="Research agent", agent_card_url="http://localhost:8001/.well-known/agent-card.json", ) result = research.invoke("What is the boiling point of nitrogen?") print(result["messages"][-1].content) ``` ## Multi-turn conversations Pass a `thread_id` to resume the same server-side A2A context across calls: ```python from langchain_core.runnables import RunnableConfig config = RunnableConfig(configurable={"thread_id": "user-42"}) result1 = research.invoke("Tell me about black holes.", config) result2 = research.invoke("How do they emit Hawki…