TAPD 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 TAPD 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 TAPD. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in TAPD?"
)
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 TAPD MCP Server
Empower your AI agent to orchestrate your agile development lifecycle with TAPD, the professional collaboration platform by Tencent. By connecting TAPD to your agent, you transform complex requirement tracking, bug management, and iteration planning into a natural conversation. Your agent can instantly list your workspaces, create new stories, track defects, and even monitor sprint progress without you ever needing to navigate the complex TAPD enterprise interface. Whether you are following Scrum or Kanban, your agent acts as a real-time product assistant, keeping your development pipeline organized and your team aligned.
LlamaIndex agents combine TAPD 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
- Workspace Management — List all accessible workspaces and retrieve detailed information about your development environment.
- Requirement Tracking — Create and track stories (requirements) with full support for titles and detailed descriptions.
- Defect Management — List and create bugs to keep your quality assurance process moving efficiently.
- Task Operations — Manage granular tasks within your workspaces to stay on top of daily development activities.
- Iteration Monitoring — Browse workspace iterations (sprints) to track project milestones and delivery schedules.
- Team Overview — List workspace members to manage assignments and collaboration effectively.
The TAPD 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 TAPD to LlamaIndex via MCP
Follow these steps to integrate the TAPD 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 TAPD
Why Use LlamaIndex with the TAPD MCP Server
LlamaIndex provides unique advantages when paired with TAPD through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine TAPD tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain TAPD tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query TAPD, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what TAPD tools were called, what data was returned, and how it influenced the final answer
TAPD + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the TAPD MCP Server delivers measurable value.
Hybrid search: combine TAPD real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query TAPD 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 TAPD for fresh data
Analytical workflows: chain TAPD queries with LlamaIndex's data connectors to build multi-source analytical reports
TAPD MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect TAPD to LlamaIndex via MCP:
create_bug
Create a new TAPD bug
create_story
Create a new TAPD story
create_task
Create a new TAPD task
get_workspace
Get workspace details
list_bugs
List bugs in a workspace
list_iterations
List workspace iterations
list_members
List workspace members
list_stories
List stories in a workspace
list_tasks
List tasks in a workspace
list_workspaces
List all TAPD workspaces
Example Prompts for TAPD in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with TAPD immediately.
"List all my active workspaces on TAPD."
"Create a new bug in workspace 'Mobile App V2' titled 'App crashes on splash screen'."
"Show me the iterations for project 'Cloud Infrastructure'."
Troubleshooting TAPD MCP Server with LlamaIndex
Common issues when connecting TAPD to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTAPD + LlamaIndex FAQ
Common questions about integrating TAPD 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 TAPD 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 TAPD to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.