KanbanTool MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Archive Task Card, Create Task Card, Get Board Details, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add KanbanTool 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 KanbanTool app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 10 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 KanbanTool. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in KanbanTool?"
)
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 KanbanTool MCP Server
Connect your KanbanTool account to any AI agent and manage kanban boards through natural conversation.
LlamaIndex agents combine KanbanTool 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
- Board Management — List all boards, inspect layouts, and configure columns
- Task Management — Create, move, update, and archive cards across columns
- Workflow Tracking — Monitor cards across workflow stages (To Do, In Progress, Done)
- Team Collaboration — Assign cards to team members and track workload
- WIP Monitoring — Track work-in-progress limits and bottlenecks
- Activity History — View card activity and changelog
The KanbanTool 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.
All 10 KanbanTool tools available for LlamaIndex
When LlamaIndex connects to KanbanTool through Vinkius, your AI agent gets direct access to every tool listed below — spanning kanban, agile, workflow-automation, 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.
Archive a task card
Add a new card to a board
Get metadata and tasks for a board
Get details for a task
Get current user profile
List tasks on a board
List your Kanban boards
List shared board links
List history for a task
Modify an existing task
Connect KanbanTool to LlamaIndex via MCP
Follow these steps to wire KanbanTool 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 KanbanTool MCP Server
LlamaIndex provides unique advantages when paired with KanbanTool through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine KanbanTool tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain KanbanTool tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query KanbanTool, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what KanbanTool tools were called, what data was returned, and how it influenced the final answer
KanbanTool + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the KanbanTool MCP Server delivers measurable value.
Hybrid search: combine KanbanTool real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query KanbanTool 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 KanbanTool for fresh data
Analytical workflows: chain KanbanTool queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for KanbanTool in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with KanbanTool immediately.
"Show all boards and the cards in the 'Sprint Board' by column."
"Create a new card 'Implement OAuth' in To Do and move 'API Rate Limiting' to Done."
"Show team workload and all cards assigned to Sarah."
Troubleshooting KanbanTool MCP Server with LlamaIndex
Common issues when connecting KanbanTool to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKanbanTool + LlamaIndex FAQ
Common questions about integrating KanbanTool MCP Server with LlamaIndex.