How to Use the ChartHop MCP in Google ADK

Q: How do I configure ChartHop with Google ADK?

Install google-adk. Setup an McpToolset using your HTTP endpoint URL. Pass the toolset directly into the tools array of your LlmAgent.

Q: Can Google ADK filter which ChartHop tools the agent sees?

Yes, the framework supports tool filtering. You pass a toolnames list to the toolset configuration to expose listorganizationjobs while blocking access to individual person details.

Give your Google ADK agents direct access to ChartHop HR data to analyze massive organizational structures using Gemini's long context.

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Connect ChartHop MCP to Google ADK

Create your Vinkius account to connect ChartHop 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 ChartHop with Google ADK

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Perplexity

Feed ChartHop data to Google ADK

Enterprise structures get complicated fast. Gemini's million-token context window eats massive hierarchies for breakfast. Your agent calls `list_organization_people` and dumps the entire roster into context for cross-department analysis. You combine this HR data with existing BigQuery datasets. An agent can pull job descriptions via `get_job_details` and compare them against internal performance metrics stored in Google Cloud.

Analyze planning scenarios

Workforce planning requires deep context. The `list_planning_scenarios` tool lets your Gemini agent read active compensation models directly from this MCP Server. It pulls the raw data so you can run complex financial projections. Integration is straightforward. You instantiate `McpToolset` with `StreamableHttpServerParameters` pointing to your Vinkius endpoint. Pass that into your `LlmAgent` and the tools are ready to fire.

Inspect departments and teams

Sometimes you just need the specifics of a single business unit. Using `list_organization_departments` and `list_organization_teams`, the agent isolates specific groups. It filters out the noise before doing deeper analysis on a specific division. You can restrict what the model sees. The ADK allows a `tool_names` filter, so you can expose `get_organization_summary` while hiding individual profile tools. This keeps the agent focused on high-level strategy over the MCP connection.

Setup guide

Set up ChartHop 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 ChartHop 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="ChartHop_agent",
    model="gemini-2.0-flash",
    instruction="You have access to ChartHop tools via MCP.",
    tools=mcp_tools,
)

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Common questions about ChartHop MCP in Google ADK

Install `google-adk`. Setup an `McpToolset` using your HTTP endpoint URL. Pass the toolset directly into the `tools` array of your `LlmAgent`.

Yes, the framework supports tool filtering. You pass a `tool_names` list to the toolset configuration to expose `list_organization_jobs` while blocking access to individual person details.

Gemini handles massive payloads easily. Your agent can execute `list_organization_people` to pull thousands of records into context at once for broad organizational reasoning.

Yes. The ADK supports both Stdio and HTTP transports. For Vinkius-managed servers, you use the Streamable HTTP parameters to connect securely.

The system reads compensation planning scenarios through a zero-trust architecture. Every request requires a valid endpoint token, and the execution environment vanishes the millisecond the response returns to your agent.

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