Babelagent

The Babel that lets AI agents understand each other. One shared tongue for agents that were never meant to talk.

Every agent framework has its own idea of what an agent is. LangChain has Runnables with .invoke, CrewAI has Crews with .kickoff, AutoGen has agents with .generate_reply, an LLM has messages.create, a microservice has an HTTP route. None of them agree on a shape, so connecting any two means writing glue.

Babelagent is the neutral layer in between. You bring your own agents, whatever they are, and it wraps each one in a single shared interface so they can exchange messages and collaborate on a task, agent-to-agent (A2A), and get graded at each hop.

import asyncio
from babelagent import Graph

async def main():
    graph = (
        Graph()
        .node("clean",   str.strip)
        .node("shout",   str.upper)
        .node("exclaim", lambda s: s + "!")
    )
    result = await graph.run("  hello  ")
    print(result.output)   # "HELLO!"

asyncio.run(main())

Why it exists

Existing frameworks each want to be your world: adopt our agent model, our memory, our orchestration. Two of them in one process fight rather than cooperate. Babelagent owns very little on purpose. It is not another framework; it is the shared tongue between them, the wiring that carries messages, and an inspector that grades each hop before it continues.

The one thing it does that nothing else ships: a per-hop, tri-state quality gate (pass / warn / fail) that can stop bad output from flowing downstream, on a framework-agnostic agent graph. See the whole story for the honest landscape (what is commodity, what is the wedge, and how it sits on top of A2A/MCP rather than against them).

Install

Requires Python 3.11+. (If your default python is older, pip install babelagent says "No matching distribution found" — use a 3.11+ interpreter: uv venv --python 3.12 && uv pip install babelagent, or uv tool install babelagent for just the CLI.)

pip install babelagent                 # light base (callables + HTTP + A2A)
pip install "babelagent[mcp]"          # MCP tools + MCP server
pip install "babelagent[cloud]"        # Anthropic / OpenAI
pip install "babelagent[frameworks]"   # LangChain (CrewAI/AutoGen detected if installed)
pip install "babelagent[serve]"        # REST service
pip install "babelagent[all]"

Try it (no API key)

$ babelagent demo
Babelagent demo — one agent, a quality gate, no API key.

broken graph → verdict=fail ok=False
  summarize: gate blocked: output is empty

fixed graph  → verdict=pass ok=True
  result: [24 words] Different agents speak different dialects, and Babelagent gives…

Concepts

Concept	What it is
Graph	Builds the network of agents (linear chaining and a DAG API)
CompiledGraph	The validated, runnable graph; await graph.run(payload)
Node	One participant: an agent plus an optional quality check/gate
Agent	The uniform async run(message, ctx) -> message interface
adapt()	Turns any brought object into an Agent, inferring the adapter
Message / Result	The envelope agents exchange / the final output + run trace
Barrier	Fan-in join policy: all · k_of_n · optional

Next: the Quickstart, the adapters guide, and agent-to-agent.

Cite

Concept DOI (always resolves to the latest version): 10.5281/zenodo.22129957.

— amitpatole