GitHub - GetBindu/Bindu: Bindu: Turn any AI agent into a living microservice - interoperable, observable, composable.

The identity, communication & payments layer for AI agents

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"Like sunflowers turning toward the light, agents collaborate in swarms - each one independent, yet together they create something greater."

Onboard your agent in one line

curl -fsSL https://getbindu.com/install-bindu.sh | bash

Bindu (read: binduu) turns any AI agent into a production microservice. Build your agent in any framework — Agno, LangChain, OpenAI SDK, even plain TypeScript — call bindufy(), and get a service with DID identity, A2A protocol, OAuth2 auth, and crypto payments. No infrastructure code. No rewriting.

Works with Python, TypeScript, and Kotlin. Built on open protocols: A2A, AP2, and X402.

🌟 Register your agent • 🌻 Documentation • 💬 Discord Community

🎥 Watch Bindu in Action

📋 Prerequisites

Before installing Bindu, ensure you have:

Python 3.12 or higher - Download here
UV package manager - Installation guide
API Key Required: Set OPENROUTER_API_KEY, OPENAI_API_KEY, or MINIMAX_API_KEY in your environment variables. Free OpenRouter models are available for testing. MiniMax AI offers M2.7 with 1M context window.

Verify Your Setup

# Check Python version
uv run python --version  # Should show 3.12 or higher

# Check UV installation
uv --version

📦 Installation

Users note (Git & GitHub Desktop)

On some Windows systems, git may not be recognized in Command Prompt even after installation due to PATH configuration issues.

If you face this issue, you can use GitHub Desktop as an alternative:

Install GitHub Desktop from https://desktop.github.com/
Sign in with your GitHub account
Clone the repository using the repository URL: https://github.com/getbindu/Bindu.git

GitHub Desktop allows you to clone, manage branches, commit changes, and open pull requests without using the command line.

# Install Bindu
uv add bindu

# For development (if contributing to Bindu)
# Create and activate virtual environment
uv venv --python 3.12.9
source .venv/bin/activate  # On macOS/Linux
# .venv\Scripts\activate  # On Windows

uv sync --dev

Common Installation Issues (click to expand)

Issue	Solution
`uv: command not found`	Restart your terminal after installing UV. On Windows, use PowerShell
`Python version not supported`	Install Python 3.12+ from python.org
Virtual environment not activating (Windows)	Use PowerShell and run `.venv\Scripts\activate`
`Microsoft Visual C++ required`	Download Visual C++ Build Tools
`ModuleNotFoundError`	Activate venv and run `uv sync --dev`

🚀 Quick Start

Option 1: Manual Setup

Create your agent script my_agent.py:

import os

from bindu.penguin.bindufy import bindufy
from agno.agent import Agent
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.models.openai import OpenAIChat

# Define your agent
agent = Agent(
    instructions="You are a research assistant that finds and summarizes information.",
    model=OpenAIChat(id="gpt-4o"),
    tools=[DuckDuckGoTools()],
)

# Configuration
config = {
    "author": "your.email@example.com",
    "name": "research_agent",
    "description": "A research assistant agent",
    "deployment": {
        "url": os.getenv("BINDU_DEPLOYMENT_URL", "http://localhost:3773"),
        "expose": True,
    },
    "skills": ["skills/question-answering", "skills/pdf-processing"]
}

# Handler function
def handler(messages: list[dict[str, str]]):
    """Process messages and return agent response.

    Args:
        messages: List of message dictionaries containing conversation history

    Returns:
        Agent response result
    """
    result = agent.run(input=messages)
    return result

# Bindu-fy it
bindufy(config, handler)

# Use tunnel to expose your agent to the internet
# bindufy(config, handler, launch=True)

Your agent is now live at the URL configured in deployment.url.

Set a custom port without code changes:

# Linux/macOS
export BINDU_PORT=4000

# Windows PowerShell
$env:BINDU_PORT="4000"

Existing examples that use http://localhost:3773 are automatically overridden when BINDU_PORT is set.

Option 2: TypeScript Agent

Same pattern, different language. Create index.ts:

import { bindufy } from "@bindu/sdk";
import OpenAI from "openai";

const openai = new OpenAI();

bindufy({
  author: "your.email@example.com",
  name: "research_agent",
  description: "A research assistant agent",
  deployment: { url: "http://localhost:3773", expose: true },
  skills: ["skills/question-answering"],
}, async (messages) => {
  const response = await openai.chat.completions.create({
    model: "gpt-4o",
    messages: messages.map(m => ({
      role: m.role as "user" | "assistant" | "system",
      content: m.content,
    })),
  });
  return response.choices[0].message.content || "";
});

Run it:

npm install @bindu/sdk openai
npx tsx index.ts

The SDK launches the Bindu core automatically in the background. Your agent is live at http://localhost:3773 — same A2A protocol, same DID, same everything.

See examples/typescript-openai-agent/ for the full working example with setup instructions.

Option 3: Zero-Config Local Agent

Try Bindu without setting up Postgres, Redis, or any cloud services. Runs entirely locally using in-memory storage and scheduler.

python examples/beginner_zero_config_agent.py

Option 4: Minimal Echo Agent (Testing)

View minimal example (click to expand)

Smallest possible working agent:

import os

from bindu.penguin.bindufy import bindufy

def handler(messages):
    return [{"role": "assistant", "content": messages[-1]["content"]}]

config = {
    "author": "your.email@example.com",
    "name": "echo_agent",
    "description": "A basic echo agent for quick testing.",
    "deployment": {
        "url": os.getenv("BINDU_DEPLOYMENT_URL", "http://localhost:3773"),
        "expose": True,
    },
    "skills": []
}

bindufy(config, handler)

# Use tunnel to expose your agent to the internet
# bindufy(config, handler, launch=True)

Run the agent:

# Start the agent
python examples/echo_agent.py

Test the agent with curl (click to expand)

Input:

curl --location 'http://localhost:3773/' \
--header 'Content-Type: application/json' \
--data '{
    "jsonrpc": "2.0",
    "method": "message/send",
    "params": {
        "message": {
            "role": "user",
            "parts": [
                {
                    "kind": "text",
                    "text": "Quote"
                }
            ],
            "kind": "message",
            "messageId": "550e8400-e29b-41d4-a716-446655440038",
            "contextId": "550e8400-e29b-41d4-a716-446655440038",
            "taskId": "550e8400-e29b-41d4-a716-446655440300"
        },
        "configuration": {
            "acceptedOutputModes": [
                "application/json"
            ]
        }
    },
    "id": "550e8400-e29b-41d4-a716-446655440024"
}'

Output:

{
    "jsonrpc": "2.0",
    "id": "550e8400-e29b-41d4-a716-446655440024",
    "result": {
        "id": "550e8400-e29b-41d4-a716-446655440301",
        "context_id": "550e8400-e29b-41d4-a716-446655440038",
        "kind": "task",
        "status": {
            "state": "submitted",
            "timestamp": "2025-12-16T17:10:32.116980+00:00"
        },
        "history": [
            {
                "message_id": "550e8400-e29b-41d4-a716-446655440038",
                "context_id": "550e8400-e29b-41d4-a716-446655440038",
                "task_id": "550e8400-e29b-41d4-a716-446655440301",
                "kind": "message",
                "parts": [
                    {
                        "kind": "text",
                        "text": "Quote"
                    }
                ],
                "role": "user"
            }
        ]
    }
}

Check the status of the task

curl --location 'http://localhost:3773/' \
--header 'Content-Type: application/json' \
--data '{
    "jsonrpc": "2.0",
    "method": "tasks/get",
    "params": {
        "taskId": "550e8400-e29b-41d4-a716-446655440301"
    },
    "id": "550e8400-e29b-41d4-a716-446655440025"
}'

Output:

{
    "jsonrpc": "2.0",
    "id": "550e8400-e29b-41d4-a716-446655440025",
    "result": {
        "id": "550e8400-e29b-41d4-a716-446655440301",
        "context_id": "550e8400-e29b-41d4-a716-446655440038",
        "kind": "task",
        "status": {
            "state": "completed",
            "timestamp": "2025-12-16T17:10:32.122360+00:00"
        },
        "history": [
            {
                "message_id": "550e8400-e29b-41d4-a716-446655440038",
                "context_id": "550e8400-e29b-41d4-a716-446655440038",
                "task_id": "550e8400-e29b-41d4-a716-446655440301",
                "kind": "message",
                "parts": [
                    {
                        "kind": "text",
                        "text": "Quote"
                    }
                ],
                "role": "user"
            },
            {
                "role": "assistant",
                "parts": [
                    {
                        "kind": "text",
                        "text": "Quote"
                    }
                ],
                "kind": "message",
                "message_id": "2f2c1a8e-68fa-4bb7-91c2-eac223e6650b",
                "task_id": "550e8400-e29b-41d4-a716-446655440301",
                "context_id": "550e8400-e29b-41d4-a716-446655440038"
            }
        ],
        "artifacts": [
            {
                "artifact_id": "22ac0080-804e-4ff6-b01c-77e6b5aea7e8",
                "name": "result",
                "parts": [
                    {
                        "kind": "text",
                        "text": "Quote",
                        "metadata": {
                            "did.message.signature": "5opJuKrBDW4woezujm88FzTqRDWAB62qD3wxKz96Bt2izfuzsneo3zY7yqHnV77cq3BDKepdcro2puiGTVAB52qf"  # pragma: allowlist secret
                        }
                    }
                ]
            }
        ]
    }
}

🚀 Core Features

Feature	Description	Documentation
🔐 Authentication	Secure API access with Ory Hydra OAuth2 (optional for development)	Guide →
💰 Payment Integration (X402)	Accept USDC payments on Base blockchain before executing protected methods	Guide →
💾 PostgreSQL Storage	Persistent storage for production deployments (optional - InMemoryStorage by default)	Guide →
📋 Redis Scheduler	Distributed task scheduling for multi-worker deployments (optional - InMemoryScheduler by default)	Guide →
🎯 Skills System	Reusable capabilities that agents advertise and execute for intelligent task routing	Guide →
🤝 Agent Negotiation	Capability-based agent selection for intelligent orchestration	Guide →
🌐 Tunneling	Expose local agents to the internet for testing (local development only, not for production)	Guide →
📬 Push Notifications	Real-time webhook notifications for task updates - no polling required	Guide →
📊 Observability & Monitoring	Track performance and debug issues with OpenTelemetry and Sentry	Guide →
🔄 Retry Mechanism	Automatic retry with exponential backoff for resilient agents	Guide →
🔑 Decentralized Identifiers (DIDs)	Cryptographic identity for verifiable, secure agent interactions and payment integration	Guide →
🏥 Health Check & Metrics	Monitor agent health and performance with built-in endpoints	Guide →
🌍 Language-Agnostic (gRPC)	Bindufy agents written in TypeScript, Kotlin, Rust, or any language via gRPC adapter	Guide →

🎨 Chat UI

Bindu includes a beautiful chat interface at http://localhost:5173. Navigate to the frontend folder and run npm run dev to start the server.

🌐 GetBindu.com

GetBindu.com is a public registry of Bindu agents — discoverable and accessible to the broader agent ecosystem. Register your agent and make it available to other agents and orchestrators.

🛠️ Supported Agent Frameworks

Bindu is framework-agnostic and tested with:

Python:

AG2 (formerly AutoGen)
Agno
CrewAI
LangChain
LlamaIndex
FastAgent

TypeScript:

OpenAI SDK
LangChain.js

Kotlin:

OpenAI Kotlin SDK

Bindu is language-agnostic via gRPC — see docs/grpc/ for how it works and how to add new languages.

Compatible LLM Providers:

OpenRouter — Access 100+ models through a single API
OpenAI — GPT-4o, GPT-5, and more
MiniMax AI — M2.7 (1M context), M2.5, M2.5-highspeed (204K context) via OpenAI-compatible API

Want integration with your favorite framework? Let us know on Discord!

🧪 Testing

Bindu maintains 70%+ test coverage (target: 80%+):

# Unit tests (fast, in pre-commit)
uv run pytest tests/unit/ -v

# E2E gRPC integration tests (real servers, full round-trip)
uv run pytest tests/integration/grpc/ -v -m e2e

# All tests with coverage
uv run pytest -n auto --cov=bindu --cov-report=term-missing
uv run coverage report --skip-covered --fail-under=70

CI runs automatically on every PR — unit tests, E2E gRPC tests, and TypeScript SDK build verification. See .github/workflows/ci.yml.

🔧 Troubleshooting

Common Issues

Issue	Solution
`Python 3.12 not found`	Install Python 3.12+ and set in PATH, or use `pyenv`
`bindu: command not found`	Activate virtual environment: `source .venv/bin/activate`
`Port 3773 already in use`	Set `BINDU_PORT=4000` or override URL with `BINDU_DEPLOYMENT_URL=http://localhost:4000`
Pre-commit fails	Run `pre-commit run --all-files`
Tests fail	Install dev dependencies: `uv sync --dev`
`Permission denied` (macOS)	Run `xattr -cr .` to clear extended attributes

Reset environment:

rm -rf .venv
uv venv --python 3.12.9
uv sync --dev

Windows PowerShell:

Set-ExecutionPolicy RemoteSigned -Scope CurrentUser

🤝 Contributing

We welcome contributions! Join us on Discord. Pick the channel that best matches your contribution.

git clone https://github.com/getbindu/Bindu.git
cd Bindu
uv venv --python 3.12.9
source .venv/bin/activate
uv sync --dev
pre-commit run --all-files

📖 Contributing Guidelines

📜 License

Bindu is open-source under the Apache License 2.0.

💬 Community

We 💛 contributions! Whether you're fixing bugs, improving documentation, or building demos—your contributions make Bindu better.

💬 Join Discord for discussions and support
⭐ Star the repository if you find it useful!

👥 Active Moderators

Our dedicated moderators help maintain a welcoming and productive community:

Want to become a moderator? Reach out on Discord!

🙏 Acknowledgements

Grateful to these projects:

🌌 The Vision

a peek into the night sky
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Each symbol is an agent — a spark of intelligence. The tiny dot is Bindu, the origin point in the Internet of Agents.

NightSky Connection (In Progress)

NightSky enables swarms of agents. Each Bindu is a dot annotating agents with the shared language of A2A, AP2, and X402. Agents can be hosted anywhere — laptops, clouds, or clusters — yet speak the same protocol, trust each other by design, and work together as a single, distributed mind.

🗺️ Roadmap

gRPC transport + language-agnostic SDKs (TypeScript, Kotlin)
Increase test coverage to 80% (in progress)
AP2 end-to-end support
DSPy integration (in progress)
Rust SDK
MLTS support
X402 support with other facilitators

💡 Suggest features on Discord!

We will make this agents bidufied and we do need your help.

🎓 Workshops

[AI Native in Action: Agent Symphony](https://www.meetup.com/ai-native-Amsterdam && India/events/311066899/) - Slides

⭐ Star History

Built with 💛 by the team from Amsterdam && India
Happy Bindu! 🌻🚀✨

From idea to Internet of Agents in 2 minutes.
Your agent. Your framework. Universal protocols.

⭐ Star us on GitHub • 💬 Join Discord • 🌻 Read the Docs

"We believe in the sunflower theory - standing tall together, bringing hope and light to the Internet of Agents."