Ayanza MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Ayanza as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Ayanza. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Ayanza?"
)
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 Ayanza MCP Server
Orchestrate your team's rhythm with Ayanza, the AI-first project management platform designed for modern velocity. By connecting Ayanza to your AI agent, you transform project oversight from a manual chore into a natural conversation. Your agent gains the power to navigate complex task workflows, access team wikis, and manage project milestones without you ever opening a dashboard. It’s not just about tracking tasks; it’s about giving your agent the context it needs to act as a digital coordinator within your workspace.
LlamaIndex agents combine Ayanza tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Task Orchestration — List, create, update, and delete tasks in Ayanza using natural language through your AI agent.
- Project Oversight — Get a comprehensive view of all projects or dive into specific project details to monitor progress effortlessly.
- Knowledge Retrieval — Access and list wiki pages to quickly find team documentation and shared knowledge.
- Workspace Management — View workspace users to understand team structure and assign tasks effectively.
- Dynamic Updates — Modify task descriptions and statuses in real-time to keep your team aligned and productive.
The Ayanza MCP Server exposes 10 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 Ayanza to LlamaIndex via MCP
Follow these steps to integrate the Ayanza 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 10 tools from Ayanza
Why Use LlamaIndex with the Ayanza MCP Server
LlamaIndex provides unique advantages when paired with Ayanza through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Ayanza tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Ayanza tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Ayanza, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Ayanza tools were called, what data was returned, and how it influenced the final answer
Ayanza + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Ayanza MCP Server delivers measurable value.
Hybrid search: combine Ayanza real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Ayanza 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 Ayanza for fresh data
Analytical workflows: chain Ayanza queries with LlamaIndex's data connectors to build multi-source analytical reports
Ayanza MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Ayanza to LlamaIndex via MCP:
create_task
Create a new task in Ayanza
delete_task
Delete an Ayanza task
get_me
Get current authenticated user info
get_project
Get details for a specific Ayanza project
get_task
Get details for a specific Ayanza task
list_projects
List projects in Ayanza
list_tasks
List tasks in Ayanza
list_users
List users in the Ayanza workspace
list_wiki_pages
List wiki pages in Ayanza
update_task
Update an existing Ayanza task
Example Prompts for Ayanza in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Ayanza immediately.
"List all my tasks in Ayanza."
"Create a new task called 'Prepare Q4 presentation'."
"Show my wiki pages in Ayanza."
Troubleshooting Ayanza MCP Server with LlamaIndex
Common issues when connecting Ayanza to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAyanza + LlamaIndex FAQ
Common questions about integrating Ayanza 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 Ayanza 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 Ayanza to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.