airfocus MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Create Airfocus Item, Get Airfocus Item, List Airfocus Fields, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add airfocus 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 App Connector for LlamaIndex
The airfocus app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 airfocus. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in airfocus?"
)
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 airfocus MCP Server
Connect your airfocus account to any AI agent and take full control of your product management and strategic roadmapping workflows through natural conversation.
LlamaIndex agents combine airfocus 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
- Workspace & Roadmap Orchestration — List all strategic workspaces programmatically, retrieving detailed metadata and custom fields tailored for every product board
- Item Lifecycle Management — Programmatically create and update tasks, features, and initiatives, monitoring status transitions and high-fidelity descriptions in real-time
- Prioritization Intelligence — Retrieve and update prioritization scores and custom field data to coordinate your product strategy and team alignment perfectly
- Cross-functional Sync — Ensure your engineering context matches product roadmaps by querying specific item details directly through your agent
- Infrastructure Monitoring — Access high-fidelity metadata for your workspaces and manage field definitions to maintain a perfectly coordinated project environment
The airfocus 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.
All 6 airfocus tools available for LlamaIndex
When LlamaIndex connects to airfocus through Vinkius, your AI agent gets direct access to every tool listed below — spanning airfocus, product-management-api, roadmaps-orchestration, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create an item
Get item details
List custom fields
List workspace items
List all workspaces
Update an item
Connect airfocus to LlamaIndex via MCP
Follow these steps to wire airfocus into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the airfocus MCP Server
LlamaIndex provides unique advantages when paired with airfocus through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine airfocus tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain airfocus tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query airfocus, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what airfocus tools were called, what data was returned, and how it influenced the final answer
airfocus + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the airfocus MCP Server delivers measurable value.
Hybrid search: combine airfocus real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query airfocus 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 airfocus for fresh data
Analytical workflows: chain airfocus queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for airfocus in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with airfocus immediately.
"List all items in the 'Product Roadmap' workspace (ID: '123')."
"Create a new feature 'User Analytics' in workspace '123'."
"Show the custom fields for workspace '123'."
Troubleshooting airfocus MCP Server with LlamaIndex
Common issues when connecting airfocus to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpairfocus + LlamaIndex FAQ
Common questions about integrating airfocus MCP Server with LlamaIndex.