How to Use the Regex Toolkit MCP in Google ADK

Q: How do I add the Regex Toolkit to my Google ADK agent?

Install the package with pip install google-adk and pass the MCP server URL to McpToolset using StreamableHttpServerParameters. Then, include this toolset in the tools list when initializing your LlmAgent.

Q: Can I restrict which tools are exposed to my agent?

Yes, you can use the optional toolnames filter inside your toolset initialization. This restricts the agent's access to only the specific utilities you want it to use, reducing tool selection errors.

Inject deterministic regex extraction and validation into your Google ADK enterprise agents to clean BigQuery pipeline data.

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Connect Regex Toolkit MCP to Google ADK

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Setup Regex Toolkit with Google ADK

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Google ADK data scrubbing with regex

The `mask_sensitive_data` tool strips out emails, telephone numbers, and web URLs from unstructured database fields by applying regex-based redaction. It swaps out these sensitive identifiers for standard `[REDACTED]` tags. This capability lets your Gemini models analyze massive text corpora safely without exposing raw customer details. By running this MCP Server, your enterprise pipeline cleans the data before it ever touches your AI model or leaves your Google Cloud VPC.

Extract clean strings from unstructured text

The `extract_pattern` tool parses massive text blocks to isolate and return unique emails, phone numbers, or URLs. It bypasses LLM text generation entirely to deliver structured arrays of matches directly to your agent. You can feed the output of this MCP Server straight into BigQuery or Vertex AI pipelines for downstream analysis. Because it relies on deterministic matching, you never have to worry about the agent hallucinating formatting or injecting non-existent domains.

Validate phone and email formats instantly

The `validate_pattern` tool evaluates whether a given string matches standard email, URL, or telephone formats. It returns a precise boolean match, allowing your agent to make immediate branching decisions. This validation prevents malformed contact info from entering your CRM or marketing databases. It provides a reliable gatekeeper for any user-submitted data your agent processes.

Setup guide

Set up Regex Toolkit 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 Regex Toolkit 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="Regex Toolkit_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Regex Toolkit 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 regex-toolkit. 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 Regex Toolkit MCP in Google ADK

Install the package with `pip install google-adk` and pass the MCP server URL to `McpToolset` using `StreamableHttpServerParameters`. Then, include this toolset in the `tools` list when initializing your `LlmAgent`.

Yes, the server processes large text payloads efficiently. Because Gemini supports long context windows, you can pass large documents to the model and have it selectively trigger the MCP tools to parse specific sections.

Yes, the server supports both Stdio and HTTP transports. For cloud-hosted enterprise agents, using the HTTP transport with a secure endpoint token is the recommended approach.

Yes, you can use the optional `tool_names` filter inside your toolset initialization. This restricts the agent's access to only the specific utilities you want it to use, reducing tool selection errors.

All text, emails, and URLs are processed in an ephemeral, zero-trust V8 isolate sandbox managed by Vinkius. Your sensitive data is never logged or written to persistent storage, maintaining strict data sovereignty.

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