How to Use the Height (Project Management) MCP in Google ADK

Q: How can I analyze team workload in Height (Project Management) using the Google ADK?

You can build an agent that first calls listusers to get a roster, then uses listtasks filtered by assignee. Because Gemini can handle large amounts of data, the agent can synthesize this information to report on individual workloads across the entire team.

Q: Can I use the Google ADK to find dependencies between tasks in Height (Project Management)?

Yes, an agent can use listtasks to fetch all tasks for a project and then call gettask on each one. By analyzing the descriptions and linked tasks within the data returned, a Gemini-powered agent can identify and map out dependencies for you.

Q: How do I limit the tools my agent can use?

When you configure the McpToolset in the Google ADK, you can pass an optional toolnames filter. This lets you restrict the agent to a specific subset of the available Height tools, like only allowing gettask.

Connect Google's Gemini to your Height workspace with the Google ADK. Analyze project data at scale using long-context agents.

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Connect Height (Project Management) MCP to Google ADK

Create your Vinkius account to connect Height (Project Management) to Google ADK 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 Google ADK

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Feed Project Data into Long-Context Models

Pull thousands of task updates directly into your Gemini agent. Use the `list_activities` tool to grab a project's entire history, or `list_tasks` to get a complete backlog. Gemini's large context window means your agent can hold all that data in memory at once. Your agent can then reason over the entire dataset to find patterns, identify bottlenecks, or generate summaries that would be impossible with smaller models. You're not just fetching data; you're giving your agent the raw material for deep analysis.

Connect Height to Your Google Cloud Workflow

This MCP server acts as a bridge between your project management and your data infrastructure. An agent can use `get_task` to pull specific ticket details from Height, then pass that structured data to a BigQuery table or a Cloud Function for further processing. It’s a straightforward way to get operational data out of a silo. You don't need to build a custom ETL pipeline. You just tell your agent what you need from Height, and it uses the tools on this server to get it.

Build Custom Enterprise Reporting Tools

The Google ADK lets you define exactly which tools your agent can access. You could expose only `list_tasks` and `list_users` to create a simple workload reporting agent. Or give it the full suite to build something that can answer complex questions about project velocity. This MCP toolset is read-only, which simplifies security and compliance. Your agents can provide visibility into your Height workspace without you having to grant them write permissions, fitting neatly into enterprise security models.

Setup guide

Set up Height (Project Management) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Height (Project Management) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Height (Project Management)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Height (Project Management) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Height (Project Management) MCP in Google ADK

You can build an agent that first calls `list_users` to get a roster, then uses `list_tasks` filtered by assignee. Because Gemini can handle large amounts of data, the agent can synthesize this information to report on individual workloads across the entire team.

No, the MCP Server connects your Google ADK agent directly to the Height API. However, a common pattern is to use the agent to pull data via tools like `list_activities` and then insert it into BigQuery for long-term analysis.

Yes, an agent can use `list_tasks` to fetch all tasks for a project and then call `get_task` on each one. By analyzing the descriptions and linked tasks within the data returned, a Gemini-powered agent can identify and map out dependencies for you.

When you configure the `McpToolset` in the Google ADK, you can pass an optional `tool_names` filter. This lets you restrict the agent to a specific subset of the available Height tools, like only allowing `get_task`.

This server reads your Height project data: task contents, project lists, user assignments, and workspace activity. Your connection is secured by Google Cloud's own identity and access management (IAM) principles, on top of the ephemeral, sandboxed environment Vinkius provides for the MCP Server itself.

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