How to Use the CRM PipeRun MCP in Google ADK

Q: How do I configure CRM PipeRun with Google ADK?

Install the google-adk package. Set up McpToolset using StreamableHttpServerParameters and your Vinkius URL, then pass it to your LlmAgent tools list.

Q: Can Gemini agents read attachments?

They use listfiles to find the document and getfile to retrieve it. You can then feed that content into Gemini's long-context window for analysis.

Q: Does Google ADK support filtering CRM PipeRun tools?

You can pass a toolnames list to the McpToolset constructor. This restricts the agent to specific operations like createactivity while blocking deletion tools.

Connect CRM PipeRun to Google ADK and let Gemini agents manage sales pipelines alongside your BigQuery data.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect CRM PipeRun MCP to Google ADK

Create your Vinkius account to connect CRM PipeRun 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.

GDPR Free for Subscribers

Setup CRM PipeRun with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Manage Activities with Google ADK

Syncing sales tasks with cloud infrastructure starts with the `list_activities` and `create_activity` tools. A Gemini agent can query a massive BigQuery dataset of user engagement metrics and immediately schedule follow-up calls in CRM PipeRun for high-scoring leads. Because Gemini handles millions of tokens, it can read entire customer histories before deciding which task to create. You configure the `McpToolset` with your Vinkius endpoint, and the agent natively understands when to trigger an update.

Process Sales Documents via MCP

Handling proposals happens through the `get_file` and `upload_file` tools. Your agent retrieves a base64 encoded contract from CRM PipeRun, analyzes the terms using Vertex AI, and uploads an amended version back to the corresponding company record. Searching through attachments uses `list_files` with built-in pagination. The agent filters documents by deal ID to find specific signed agreements without pulling irrelevant files into the context window.

Maintain Clean Sales Records

Removing outdated pipeline data requires `delete_activity` and `delete_file`. When an enterprise agent detects a merged account in your database, it clears out duplicate appointments and obsolete attachments in the CRM. Fetching the exact details of a task relies on `get_activity`. The agent pulls the specific appointment metadata, compares it against Google Workspace calendars, and makes corrections using `update_activity`.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by PipeRun. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect CRM PipeRun now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about CRM PipeRun MCP in Google ADK

Install the `google-adk` package. Set up `McpToolset` using `StreamableHttpServerParameters` and your Vinkius URL, then pass it to your `LlmAgent` tools list.

They use `list_files` to find the document and `get_file` to retrieve it. You can then feed that content into Gemini's long-context window for analysis.

You can pass a `tool_names` list to the `McpToolset` constructor. This restricts the agent to specific operations like `create_activity` while blocking deletion tools.

Your agent accesses both systems simultaneously. It runs a SQL query via Google Cloud tools, then uses `create_activity` to log tasks for the results.

Deal metadata and appointment schedules route through ephemeral Vinkius sandboxes. The connection uses zero-trust architecture, meaning your Google Cloud environment communicates securely without exposing persistent credentials.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript