How to Use the Clio MCP in Google ADK

Q: How do I configure Clio with the Google ADK?

Install google-adk via pip. Initialize McpToolset with StreamableHttpServerParameters pointing to your Vinkius URL. Pass that toolset to your LlmAgent setup.

Q: Can Gemini search for specific legal matters?

The agent uses searchmatters to find cases by keyword or partial name. It pulls full case details, including the responsible attorney, using getmatter.

Q: Does the Google ADK support filtering Clio MCP tools?

You use the toolnames parameter to restrict exposed operations. If you only want Gemini reading data, you block write tools like createtask and creatematter.

Q: How do I track firm revenue using the Clio MCP server with Google ADK?

Your agent runs listbills to monitor outstanding receivables across the firm. It pulls specific line items with getbill and cross-references that data with your BigQuery tables.

Give your Gemini agents direct access to your legal practice using the Google ADK and BigQuery.

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Setup Clio with Google ADK

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Connect the Clio MCP Server to Gemini

Enterprise legal teams already keep massive datasets in BigQuery. You connect this MCP Server using `McpToolset` so Gemini can pull live case updates and cross-reference them with your cloud data. The massive context window means the agent digests entire case histories at once. You pass the toolset to `LlmAgent` and let Gemini handle the reasoning. If a lawyer needs to find a specific witness, the agent runs `search_contacts` and parses the results. It filters out irrelevant data before returning the exact phone number.

Audit firm communications

Finding critical emails buried in a case file takes hours. Your agent calls `list_communications` to pull subjects, body text, and dates linked to specific matters. It reads the whole thread and summarizes the strategy decisions. Document discovery works the same way. The agent hits `list_documents` to find every file attached to a case. You use the `tool_names` filter to restrict the agent so it only runs read operations during an audit.

Map out case lifecycles

Tracking how long cases sit in discovery requires pulling data across the whole firm. Gemini uses `list_matter_stages` to see the exact status of every open file. It groups these by practice area using `list_practice_areas`. You get a clear view of firm bottlenecks. The agent checks `list_notes` for internal updates on stalled cases. It then writes a summary report directly to your Vertex AI dashboard.

Setup guide

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

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Common questions about Clio MCP in Google ADK

Install `google-adk` via pip. Initialize `McpToolset` with `StreamableHttpServerParameters` pointing to your Vinkius URL. Pass that toolset to your `LlmAgent` setup.

The agent uses `search_matters` to find cases by keyword or partial name. It pulls full case details, including the responsible attorney, using `get_matter`.

You use the `tool_names` parameter to restrict exposed operations. If you only want Gemini reading data, you block write tools like `create_task` and `create_matter`.

Your agent runs `list_bills` to monitor outstanding receivables across the firm. It pulls specific line items with `get_bill` and cross-references that data with your BigQuery tables.

Vinkius handles the connection through an ephemeral V8 Isolate Sandbox. When your agent pulls physical addresses and phone numbers via `get_contact`, it happens over a zero-trust HTTP transport. The session terminates immediately after the request finishes.

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