by universal-mcp
Provides a standardized interface for interacting with Google Search Console tools and services via a unified API using the Universal MCP framework.
It implements a Google Search Console MCP server that exposes Search Console data and actions through a consistent, protocol‑driven API, enabling seamless integration with other MCP‑compliant tools.
uv sync
).source .venv/bin/activate
on Unix, .venv\Scripts\Activate
on Windows).mcp dev src/universal_mcp_google_searchconsole/server.py
to view the running address.mcp install src/universal_mcp_google_searchconsole/server.py
.uv
and built‑in MCP commands.src/universal_mcp_google_searchconsole/README.md
.Q: Which Python version is required? A: Python 3.11 or newer.
Q: Do I need to set any environment variables?
A: The .env
file can hold your Google API credentials (e.g., GOOGLE_CLIENT_ID
, GOOGLE_CLIENT_SECRET
).
Q: Can I deploy this server to a cloud platform?
A: Yes—once the virtual environment is prepared, run the same mcp dev
command on the target host.
Q: Is there a Docker image available? A: Not provided in the repository, but you can containerize the project using the standard Python base image.
Q: How do I contribute? A: Fork the repository, make changes, and submit a pull request. All contributions must comply with the MIT license.
This repository contains an implementation of an Google SearchConsole Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Google SearchConsole's tools and services through a unified API.
The server is built using the Universal MCP framework.
This implementation follows the MCP specification, ensuring compatibility with other MCP-compliant services and tools.
You can start using Google SearchConsole directly from agentr.dev. Visit agentr.dev/apps and enable Google SearchConsole.
If you have not used universal mcp before follow the setup instructions at agentr.dev/quickstart
The full list of available tools is at ./src/universal_mcp_google_searchconsole/README.md
Ensure you have the following before you begin:
pip install uv
)Follow the steps below to set up your development environment:
Sync Project Dependencies
uv sync
This installs all dependencies from pyproject.toml
into a local virtual environment (.venv
).
Activate the Virtual Environment
For Linux/macOS:
source .venv/bin/activate
For Windows (PowerShell):
.venv\Scripts\Activate
Start the MCP Inspector
mcp dev src/universal_mcp_google_searchconsole/server.py
This will start the MCP inspector. Make note of the address and port shown in the console output.
Install the Application
mcp install src/universal_mcp_google_searchconsole/server.py
.
├── src/
│ └── universal_mcp_google_searchconsole/
│ ├── __init__.py # Package initializer
│ ├── server.py # Server entry point
│ ├── app.py # Application tools
│ └── README.md # List of application tools
├── tests/ # Test suite
├── .env # Environment variables for local development
├── pyproject.toml # Project configuration
└── README.md # This file
This project is licensed under the MIT License.
Generated with MCP CLI — Happy coding! 🚀
Please log in to share your review and rating for this MCP.
Discover more MCP servers with similar functionality and use cases
by exa-labs
Provides a Model Context Protocol server that enables AI assistants to perform real‑time web searches via the Exa AI Search API, with optional company research, LinkedIn lookup, and deep research workflows.
by perplexityai
Provides real-time web search capabilities to AI models via the Perplexity Sonar API, enabling seamless integration within the Model Context Protocol ecosystem.
by brightdata
Provides real‑time web access, bypasses geo‑restrictions, handles bot detection, and offers browser automation for LLMs and AI agents via the Model Context Protocol.
by mamertofabian
mcp-everything-search is a cross-platform MCP server that provides fast and flexible file searching capabilities. It leverages native system tools to efficiently locate files and folders across Windows, macOS, and Linux.
by kagisearch
Provides web search and video summarization capabilities via the Model Context Protocol, integrating with Claude and other AI tools.
by apify
mcp-server-rag-web-browser is an MCP server for the RAG Web Browser Actor, enabling AI agents and LLMs to perform web searches and extract information from web pages.
by fatwang2
Provides web and news search, URL crawling, sitemap extraction, reasoning, and trending tools via Search1API, exposed as an MCP server for seamless integration with clients such as LibreChat, Claude Desktop, Cursor, and other MCP‑compatible tools.
by meilisearch
Enables LLMs to manage Meilisearch indexes, perform searches, and handle documents through natural‑language conversations via a Model Context Protocol server.
by ihor-sokoliuk
mcp-searxng is an MCP (Model Context Protocol) server that integrates with SearXNG to provide web search capabilities for AI models and applications.