How do I query cycle time for a specific team?

Use the `query_software_metrics` tool and include the team name or ID in the `group_by` parameter of your JSON query.

What is the difference between coding_time and pickup_time?

Coding time is the duration from the first commit to the PR creation. Pickup time is the duration from the PR creation to the first review activity.

Can I report a release from the agent?

Absolutely. Use the `record_new_deployment` tool with the Git SHA or tag and the repository ID to inform LinearB that a deployment has occurred.

LinearB MCP Server for Google ADK 7 tools — connect in under 2 minutes

Name: LinearB
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 7 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add LinearB as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="linearb_agent",
    instruction=(
        "You help users interact with LinearB "
        "using 7 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About LinearB MCP Server

Connect your LinearB account to any AI agent to automate your engineering intelligence and DORA metrics reporting. This MCP server enables your agent to query cycle time, track deployments, and report incidents directly from natural language interfaces.

Google ADK natively supports LinearB as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 7 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Metric Ingestion — Query complex engineering metrics including cycle time, coding time, and pickup time across teams
Deployment Management — Inform LinearB of new software releases by reporting Git refs (SHAs or tags) programmatically
Incident Tracking — Report and list engineering incidents to maintain accurate Change Failure Rate and MTTR metrics
Metadata Oversight — List teams and connected repositories to map technical IDs to organizational structures
DORA Analytics — Retrieve aggregated performance data to identify bottlenecks in your delivery pipeline

The LinearB MCP Server exposes 7 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect LinearB to Google ADK via MCP

Follow these steps to integrate the LinearB MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 7 tools from LinearB via MCP

Why Use Google ADK with the LinearB MCP Server

Google ADK provides unique advantages when paired with LinearB through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with LinearB

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine LinearB tools with BigQuery, Vertex AI, and Cloud Functions

LinearB + Google ADK Use Cases

Practical scenarios where Google ADK combined with the LinearB MCP Server delivers measurable value.

Enterprise data agents: ADK agents query LinearB and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine LinearB tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query LinearB regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including LinearB

LinearB MCP Tools for Google ADK (7)

These 7 tools become available when you connect LinearB to Google ADK via MCP:

list_connected_repos

List all connected repositories

list_engineering_teams

List all teams defined in LinearB

list_software_deployments

List recent deployments

list_software_incidents

List engineering incidents

query_software_metrics

Requires a JSON body with requested_metrics and time_ranges. Query software engineering metrics (v2)

record_new_deployment

Requires repo_id and ref. Report a new deployment to LinearB

record_new_incident

Requires provider_id and started_at. Report a new incident

Example Prompts for LinearB in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with LinearB immediately.

"Query the average cycle_time for the last 30 days for team 'Backend'."

"Record a new deployment for repo ID '123' with Git ref 'v1.2.0'."

"Report a new incident starting now for provider 'OpsGenie'."

Troubleshooting LinearB MCP Server with Google ADK

Common issues when connecting LinearB to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

LinearB + Google ADK FAQ

Common questions about integrating LinearB MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.