Avaza MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Avaza as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Avaza. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Avaza?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Avaza MCP Server
Connect your Avaza account to any AI agent and manage your entire professional services lifecycle through natural conversation.
LlamaIndex agents combine Avaza tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Project & Task Operations — Create, update, and list projects and tasks to keep your team aligned and on schedule
- Smart Time Tracking — Log and audit timesheet entries for accurate resource management and billing
- CRM & Financial Insights — Access company contacts and retrieve recent invoices for full visibility into project financials
- Resource Coordination — Programmatically manage your professional services workflows and team allocations
The Avaza MCP Server exposes 11 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Avaza to LlamaIndex via MCP
Follow these steps to integrate the Avaza MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 11 tools from Avaza
Why Use LlamaIndex with the Avaza MCP Server
LlamaIndex provides unique advantages when paired with Avaza through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Avaza tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Avaza tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Avaza, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Avaza tools were called, what data was returned, and how it influenced the final answer
Avaza + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Avaza MCP Server delivers measurable value.
Hybrid search: combine Avaza real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Avaza to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Avaza for fresh data
Analytical workflows: chain Avaza queries with LlamaIndex's data connectors to build multi-source analytical reports
Avaza MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Avaza to LlamaIndex via MCP:
create_project
Create a new project
create_task
Create a new task in a project
create_timesheet
Create a new timesheet entry
get_account_check
Verify Avaza account connection
get_project
Get details for a specific project
list_contacts
List company contacts and users
list_invoices
List recent invoices
list_projects
List all Avaza projects
list_tasks
List all Avaza tasks
list_timesheets
List timesheet entries
update_task
Update an existing task
Example Prompts for Avaza in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Avaza immediately.
"List all active projects in Avaza."
"Create a new task 'Prepare Financial Audit' in project ID 12345."
"Log 2 hours of work for today on project 'Website Redesign'."
Troubleshooting Avaza MCP Server with LlamaIndex
Common issues when connecting Avaza to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAvaza + LlamaIndex FAQ
Common questions about integrating Avaza MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Avaza with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Avaza to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.