pip install go-micro-llamaindex

# Start MCP gateway
micro mcp serve --address :3000

from go_micro_llamaindex import GoMicroToolkit
from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI

# Initialize toolkit from MCP gateway
toolkit = GoMicroToolkit.from_gateway("http://localhost:3000")

# Create agent
llm = OpenAI(model="gpt-4")
agent = ReActAgent.from_tools(toolkit.get_tools(), llm=llm, verbose=True)

# Use the agent!
response = agent.chat("Create a user named Alice with email [email protected]")
print(response)

from go_micro_llamaindex import GoMicroToolkit

# Connect to MCP gateway
toolkit = GoMicroToolkit.from_gateway("http://localhost:3000")

# List available tools
for tool in toolkit.get_tools():
    print(f"Tool: {tool.metadata.name}")
    print(f"Description: {tool.metadata.description}")
    print()

from go_micro_llamaindex import GoMicroToolkit

# Create toolkit with authentication
toolkit = GoMicroToolkit.from_gateway(
    gateway_url="http://localhost:3000",
    auth_token="your-bearer-token"
)

# Tools will automatically use the auth token
tools = toolkit.get_tools()

from go_micro_llamaindex import GoMicroToolkit

toolkit = GoMicroToolkit.from_gateway("http://localhost:3000")

# Get only user service tools
user_tools = toolkit.get_tools(service_filter="users")

# Get tools matching a pattern
blog_tools = toolkit.get_tools(name_pattern="blog.*")

from go_micro_llamaindex import GoMicroToolkit

toolkit = GoMicroToolkit.from_gateway("http://localhost:3000")

# Select specific tools
selected_tools = toolkit.get_tools(
    include=["users.Users.Get", "users.Users.Create"]
)

# Exclude certain tools
filtered_tools = toolkit.get_tools(
    exclude=["users.Users.Delete"]
)

from go_micro_llamaindex import GoMicroToolkit
from llama_index.core import VectorStoreIndex, Document
from llama_index.core.agent import ReActAgent
from llama_index.core.tools import QueryEngineTool, ToolMetadata
from llama_index.llms.openai import OpenAI

toolkit = GoMicroToolkit.from_gateway("http://localhost:3000")

# Combine service tools with a RAG query engine
index = VectorStoreIndex.from_documents([...])
rag_tool = QueryEngineTool(
    query_engine=index.as_query_engine(),
    metadata=ToolMetadata(name="docs", description="Search documentation"),
)

all_tools = [rag_tool] + toolkit.get_tools()
agent = ReActAgent.from_tools(all_tools, llm=OpenAI(model="gpt-4"))

from go_micro_llamaindex import GoMicroToolkit
from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI

toolkit = GoMicroToolkit.from_gateway("http://localhost:3000")
llm = OpenAI(model="gpt-4")

# Agent 1: User management
user_agent = ReActAgent.from_tools(
    toolkit.get_tools(service_filter="users"), llm=llm
)

# Agent 2: Blog management
blog_agent = ReActAgent.from_tools(
    toolkit.get_tools(service_filter="blog"), llm=llm
)

# Coordinate between agents
user_result = user_agent.chat("Create user Alice")
blog_result = blog_agent.chat(f"Create blog post for {user_result}")

from go_micro_llamaindex import GoMicroToolkit, GoMicroError

try:
    toolkit = GoMicroToolkit.from_gateway("http://localhost:3000")
    tools = toolkit.get_tools()
except GoMicroError as e:
    print(f"Error: {e}")

from go_micro_llamaindex import GoMicroToolkit, GoMicroConfig

config = GoMicroConfig(
    gateway_url="http://localhost:3000",
    auth_token="your-token",
    timeout=30,
    retry_count=3,
    retry_delay=1.0,
    verify_ssl=True,
)

toolkit = GoMicroToolkit(config)
tools = toolkit.get_tools()

git clone https://github.com/micro/go-micro
cd go-micro/contrib/go-micro-llamaindex

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e ".[dev]"

# Run all tests
pytest

# Run with coverage
pytest --cov=go_micro_llamaindex

# Run specific test
pytest tests/test_toolkit.py

# Format code
black go_micro_llamaindex tests

# Check types
mypy go_micro_llamaindex

# Lint
ruff check go_micro_llamaindex

curl http://localhost:3000/health

curl http://localhost:3000/mcp/tools