Height (Project Management) 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 Height (Project Management) as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Height (Project Management). "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Height (Project Management)?"
)
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 Height (Project Management) MCP Server
Connect your Height workspace to any AI agent and take full control of your project management workflow through natural conversation.
LlamaIndex agents combine Height (Project Management) tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through the 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 Management — List, retrieve, and inspect tasks with their full metadata and structural details directly from your agent
- Lists & Grouping — Discover and manage high-level grouping constructs and lists to organize your workspace effectively
- Workspace Audit — Extract explicit workspace domains and user credentials linked to your account for quick audits
- Activity Tracking — Access full audit trails and activity logs for any task to monitor its history and state mutations
- Team Collaboration — Fetch and map registered teammates and user identities across the organization securely
The Height (Project Management) 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 Height (Project Management) to LlamaIndex via MCP
Follow these steps to integrate the Height (Project Management) 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 Height (Project Management)
Why Use LlamaIndex with the Height (Project Management) MCP Server
LlamaIndex provides unique advantages when paired with Height (Project Management) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Height (Project Management) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Height (Project Management) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Height (Project Management), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Height (Project Management) tools were called, what data was returned, and how it influenced the final answer
Height (Project Management) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Height (Project Management) MCP Server delivers measurable value.
Hybrid search: combine Height (Project Management) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Height (Project Management) 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 Height (Project Management) for fresh data
Analytical workflows: chain Height (Project Management) queries with LlamaIndex's data connectors to build multi-source analytical reports
Height (Project Management) MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect Height (Project Management) to LlamaIndex via MCP:
get_task
Get task
list_activities
List activities
list_lists
List lists
list_tasks
List tasks
list_users
List users
workspace
Get workspace
Example Prompts for Height (Project Management) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Height (Project Management) immediately.
"List all tasks in my 'Product Roadmap' list"
"Show me the recent activity for task T-102"
"What are the details for task T-108?"
Troubleshooting Height (Project Management) MCP Server with LlamaIndex
Common issues when connecting Height (Project Management) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHeight (Project Management) + LlamaIndex FAQ
Common questions about integrating Height (Project Management) 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 Height (Project Management) 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.
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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 Height (Project Management) to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.