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Getting Started

This guide shows how to install and start using Protolink.

Installation

Protolink is published on PyPI and can be installed with either uv (recommended) or pip.

Basic Installation

This installs the base package without optional extras:

# Using uv (recommended)
uv add protolink

# Using pip
pip install protolink

Optional Dependencies

Protolink exposes several extras to enable additional functionality:

# Install with all optional dependencies
uv add "protolink[all]"

# HTTP support (for web-based agents)
uv add "protolink[http]"

# All supported LLM libraries
uv add "protolink[llms]"

# Development (all extras + testing tools)
uv add "protolink[dev]"

# Install with all optional dependencies
pip install -e "protolink[all]"

# HTTP support (for web-based agents)
pip install -e "protolink[http]"

# All supported LLM libraries
pip install -e "protolink[llms]"

# Development (all extras + testing tools)
pip install -e "protolink[dev]"

Because.. why not?

# Install with all optional dependencies
uv pip install -e "protolink[all]"

# HTTP support (for web-based agents)
uv pip install -e "protolink[http]"

# All supported LLM libraries
uv pip install -e "protolink[llms]"

# Development (all extras + testing tools)
uv pip install -e "protolink[dev]"

Optional extras

You usually only need the extras that match your use case. The protolink[llms] will install all the supported LLM libraries (OpenAI, Anthropic, Ollama etc.) so it is advised to install manually the libraries that are needed for your project.

For development from source:

git clone https://github.com/nmaroulis/protolink.git
cd protolink
uv pip install -e ".[dev]"

Basic Example

Below is a minimal example that wires together an agent, HTTP transport, an OpenAI LLM, and both native and MCP tools:

from protolink.agents import Agent
from protolink.models import AgentCard
from protolink.transport import HTTPTransport
from protolink.tools.adapters import MCPToolAdapter
from protolink.llms.api import OpenAILLM


# Define the agent card
agent_card = AgentCard(
    name="example_agent",
    description="A dummy agent",
)


# Initialize the transport
transport = HTTPTransport()


# OpenAI API LLM
llm = OpenAILLM(model="gpt-5.2")


# Initialize the agent
agent = Agent(agent_card, transport, llm)


# Add Native tool
@agent.tool(name="add", description="Add two numbers")
async def add_numbers(a: int, b: int):
    return a + b


# Add MCP tool
mcp_tool = MCPToolAdapter(mcp_client, "multiply")
agent.add_tool(mcp_tool)


# Start the agent
agent.start()

This example demonstrates the core pieces of Protolink:

  • AgentCard to describe the agent.
  • Transport (here HTTPTransport) to handle A2A (agent-to-agent) communication.
  • LLM backend (OpenAILLM).
  • Native tools (Python functions decorated with @agent.tool).
  • MCP tools registered via MCPToolAdapter.