How to Use the Bitbucket MCP in Google ADK

Q: How do I add Bitbucket tools to my Google ADK agent?

Install google-adk and define an McpToolset using StreamableHttpServerParameters with your Vinkius URL. Pass this toolset into your LlmAgent constructor to expose the repository tools.

Q: Can I limit which Bitbucket tools my Google ADK agent can access?

Yes. You can use the toolnames filter in your McpToolset configuration. This restricts the agent to specific actions, like only allowing listbranches while blocking pull request modifications.

Feed your Google ADK agents whole Bitbucket repositories and track pipelines using Gemini's massive million-token context window.

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Connect Bitbucket MCP to Google ADK

Create your Vinkius account to connect Bitbucket 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 Bitbucket with Google ADK

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Long-Context Analysis via Google ADK

The `list_commits` tool feeds entire development histories directly into Gemini's million-token context window. This allows your Google ADK agent to analyze months of repository activity at once, finding patterns that shorter-context models miss. By combining this with `get_repository`, the agent maps out the structure of your codebase using this MCP Server. It cross-references commit messages with BigQuery data to generate deep insights about your team's shipping velocity.

Cloud-Scale Pipeline Auditing with Google ADK

Your agent uses the `list_pipelines` tool to monitor CI/CD runs and export build statuses straight to Vertex AI. This integration lets you train predictive models on your deployment success rates over time. When a pipeline fails, `list_pull_requests` helps the agent identify the exact pull request that triggered the build. The Google ADK framework then logs these metrics directly into your Google Cloud operations suite.

Workspace Mapping with this Bitbucket MCP Server

The `list_workspaces` tool queries all accessible areas to build an index of your enterprise code assets. Your Google ADK agent processes this list to find untracked repositories or outdated branches across your organization. Using `get_user_profile` alongside these workspace checks ensures your agent maps code ownership accurately. This helps you maintain strict compliance and clear ownership records across your cloud-hosted environments.

Setup guide

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

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

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Common questions about Bitbucket MCP in Google ADK

Install `google-adk` and define an `McpToolset` using `StreamableHttpServerParameters` with your Vinkius URL. Pass this toolset into your `LlmAgent` constructor to expose the repository tools.

Yes. You can use the `tool_names` filter in your `McpToolset` configuration. This restricts the agent to specific actions, like only allowing `list_branches` while blocking pull request modifications.

It allows your Google ADK agent to ingest the complete output of `list_commits` and `list_pull_requests` at once. The model reasons over your entire development timeline without hitting token limits.

Yes, it supports both. For managed cloud deployments on Vertex AI, we recommend using the Streamable HTTP transport to connect your agents to the Vinkius MCP Server.

All connections pass through secure HTTPS endpoints directly to the Bitbucket API. Vinkius processes your workspace lists and commit data in memory without persistent storage, keeping your proprietary code metadata isolated.

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