How to Use the Height (Project Management) MCP in LlamaIndex

Q: Can LlamaIndex query specific Height (Project Management) lists?

Yes, the agent can use listlists to find the correct ID, then pass that to listtasks. This narrows down the data before it gets embedded into your vector store.

Q: Does LlamaIndex support filtering which tools the agent can use?

Yes. You can apply an allowedtools filter when passing the spec to your agent. This prevents the LLM from wasting tokens on endpoints like listusers if you only care about task data.

Index your Height project data into LlamaIndex vector stores for semantic search.

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Connect Height (Project Management) MCP to LlamaIndex

Create your Vinkius account to connect Height (Project Management) to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Height (Project Management) with LlamaIndex

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Index Tasks with the MCP Server

The `list_tasks` and `get_task` tools extract your project tickets so LlamaIndex can embed them into a searchable vector store. You connect the server, and your RAG application pulls the raw data. It turns scattered project updates into a unified knowledge base. Users can then query past decisions without knowing exact ticket numbers. The agent retrieves the most relevant task descriptions based on semantic meaning. You stop digging through old project boards to find out why a feature was delayed.

Embed Workspace Context

The `workspace` and `list_lists` tools expose the structural metadata of your Height environment. LlamaIndex uses this data to understand how different tasks group together. It grounds the LLM responses in actual API data rather than guessing project structures. This metadata makes filtering much more accurate. When a user asks about a specific list, the agent knows exactly which subset of embedded documents to search. Results stay relevant and hallucination-free.

Map Activity and Users

The `list_activities` tool tracks the history of changes across your workspace. Your agent indexes these logs to build a timeline of project momentum. If someone asks when a bug was introduced, the RAG system checks the activity trail. You pair this with `list_users` to attribute those changes to specific team members. The agent cross-references the author of a change with the ticket context. It gives you a complete picture of who did what and why.

Setup guide

Set up Height (Project Management) MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Height (Project Management) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Height (Project Management) tools.",
)
response = await agent.run("List recent Height (Project Management) data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Height. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Height (Project Management) MCP in LlamaIndex

Initialize a BasicMCPClient with your server URL. Wrap it in an McpToolSpec and call to_tool_list_async() to expose the endpoints to your FunctionAgent.

Yes, the agent can use list_lists to find the correct ID, then pass that to list_tasks. This narrows down the data before it gets embedded into your vector store.

That depends on your project velocity. Most teams run a daily sync using the activity endpoints to catch new updates. Real-time RAG applications might poll the server more frequently.

Yes. You can apply an allowed_tools filter when passing the spec to your agent. This prevents the LLM from wasting tokens on endpoints like list_users if you only care about task data.

Your workspace IDs, user lists, and task contents never leave the encrypted execution boundary. Vinkius provisions a zero-trust environment for the connection. The data only persists in your own vector store, nowhere else.

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