Yodiz MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Yodiz 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 Yodiz. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Yodiz?"
)
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 Yodiz MCP Server
Connect your Yodiz account to any AI agent and manage your agile development lifecycle through natural conversation.
LlamaIndex agents combine Yodiz tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Requirement Tracking — List and browse user stories within your projects to monitor requirements and backlog items
- Release Management — Browse all sprints (iterations) and retrieve sprint IDs to monitor release timelines and progress
- Defect Monitoring — List and track bugs and technical debt items for any specific project ID to ensure software quality
- Roadmap Planning — Access epics to see the macro-level roadmap and strategic business goals directly from your agent
- Project Discovery — List all agile projects and workspaces to retrieve numeric IDs for granular task management
- Team Directory — List all registered users in your workspace to find colleague IDs for task assignment and mentions
- Agile Insights — Quickly surface high-level features and iteration details required for automated project reporting
The Yodiz MCP Server exposes 6 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 Yodiz to LlamaIndex via MCP
Follow these steps to integrate the Yodiz 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 6 tools from Yodiz
Why Use LlamaIndex with the Yodiz MCP Server
LlamaIndex provides unique advantages when paired with Yodiz through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Yodiz tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Yodiz tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Yodiz, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Yodiz tools were called, what data was returned, and how it influenced the final answer
Yodiz + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Yodiz MCP Server delivers measurable value.
Hybrid search: combine Yodiz real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Yodiz 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 Yodiz for fresh data
Analytical workflows: chain Yodiz queries with LlamaIndex's data connectors to build multi-source analytical reports
Yodiz MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect Yodiz to LlamaIndex via MCP:
list_bugs
Lists bugs and issues for a specific project
list_epics
Lists epics (high-level features) for a project
list_projects
Lists all agile projects in the Yodiz account
list_sprints
Lists all sprints (iterations) for a specific project
list_user_stories
Provide the numeric project ID. Lists user stories for a specific Yodiz project
list_users
Lists all registered users in the Yodiz workspace
Example Prompts for Yodiz in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Yodiz immediately.
"List all active projects in Yodiz."
"Show me the user stories for project ID 102."
"What sprints are scheduled for project ID 101?"
Troubleshooting Yodiz MCP Server with LlamaIndex
Common issues when connecting Yodiz to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpYodiz + LlamaIndex FAQ
Common questions about integrating Yodiz 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 Yodiz 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 Yodiz to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.