bindu 2026.9.2.2

A protocol framework for agent-to-agent communication

The identity, communication & payments layer for AI agents

🇬🇧 English • 🇩🇪 Deutsch • 🇪🇸 Español • 🇫🇷 Français • 🇮🇳 हिंदी • 🇮🇳 বাংলা • 🇨🇳 中文 • 🇳🇱 Nederlands • 🇮🇳 தமிழ்

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Bindu (read: binduu) is an operating layer for AI agents that provides identity, communication, and payment capabilities. It delivers a production-ready service with a convenient API to connect, authenticate, and orchestrate agents across distributed systems using open protocols: A2A, AP2, and X402.

Built with a distributed architecture (Task Manager, scheduler, storage), Bindu makes it fast to develop and easy to integrate with any AI framework. Transform any agent framework into a fully interoperable service for communication, collaboration, and commerce in the Internet of Agents.

🌟 Register your agent • 🌻 Documentation • 💬 Discord Community

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🎥 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 or OPENAI_API_KEY in your environment variables. Free OpenRouter models are available for testing.

Verify Your Setup

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

# Check UV installation
uv --version

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📦 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:

1. Install GitHub Desktop from https://desktop.github.com/
2. Sign in with your GitHub account
3. 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

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🚀 Quick Start

Option 1: Using Cookiecutter (Recommended)

Time to first agent: ~2 minutes ⏱️

# Install cookiecutter
uv add cookiecutter

# Create your Bindu agent
uvx cookiecutter https://github.com/getbindu/create-bindu-agent.git

Your local agent becomes a live, secure, discoverable service. Learn more →

💡 Pro Tip: Agents created with cookiecutter include GitHub Actions that automatically register your agent in the Bindu Directory when you push to your repository.

Option 2: Manual Setup

Create your agent script my_agent.py:

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": "[e-mail]",
    "name": "research_agent",
    "description": "A research assistant agent",
    "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 http://localhost:3773 and ready to communicate with other agents.

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:

from bindu.penguin.bindufy import bindufy

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

config = {
    "author": "[e-mail]",
    "name": "echo_agent",
    "description": "A basic echo agent for quick testing.",
    "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
                        }
                    }
                ]
            }
        ]
    }
}

 

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🚀 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 →

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🎨 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.

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🌐 Bindu Directory

The Bindu Directory is a public registry of all Bindu agents, making them discoverable and accessible to the broader agent ecosystem.

✨ Automatic Registration with Cookiecutter

When you create an agent using the cookiecutter template, it includes a pre-configured GitHub Action that automatically registers your agent in the directory:

1. Create your agent using cookiecutter
2. Push to GitHub - The GitHub Action triggers automatically
3. Your agent appears in the Bindu Directory

Note: Collect your BINDU_PAT_TOKEN from bindus.directory to register your agent.

📝 Manual Registration

Manual registration process is currently in development.

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🌌 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.

💭 A Goal Without a Plan Is Just a Wish.

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🛠️ Supported Agent Frameworks

Bindu is framework-agnostic and tested with:

• Agno
• CrewAI
• LangChain
• LlamaIndex
• FastAgent

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

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🧪 Testing

Bindu maintains 64%+ test coverage:

uv run pytest -n auto --cov=bindu --cov-report= && coverage report --skip-covered --fail-under=64

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🔧 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	Change port in config: "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

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🤝 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

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📜 License

Bindu is open-source under the Apache License 2.0.

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💬 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!

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👥 Active Moderators

Our dedicated moderators help maintain a welcoming and productive community:

Raahul Dutta

Paras Chamoli

Gaurika Sethi

Abhijeet Singh Thakur

Want to become a moderator? Reach out on Discord!

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🙏 Acknowledgements

Grateful to these projects:

• FastA2A
• 12 Factor Agents
• A2A
• AP2
• Huggingface chatui
• X402
• Bindu Logo
• ASCII Space Art

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🗺️ Roadmap

• GRPC transport support
• Increase test coverage to 80% (in progress)
• AP2 end-to-end support
• DSPy integration (in progress)
• MLTS support
• X402 support with other facilitators

💡 Suggest features on Discord!

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

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🎓 Workshops

• AI Native in Action: Agent Symphony - Slides

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⭐ Star History

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Built with 💛 by the team from Amsterdam
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