Django Firebase MCP
D

Django Firebase MCP

A Django application that implements a Firebase Model Context Protocol (MCP) server, enabling AI agents to interact with Firebase services through a standardized protocol and providing 14 tools such as authentication, database, and storage.
2 points
7.8K

What is the Django Firebase MCP Server?

The Django Firebase MCP server is a specially built system that allows AI agents to interact with Firebase services through a standardized protocol. It provides a complete set of tools and interfaces, enabling developers to easily integrate Firebase features into their AI applications.

How to use the Django Firebase MCP Server?

To use the Django Firebase MCP server, you need to set up a Firebase project and configure the necessary environment variables first. Then, you can start the server by running the provided script and interact with Firebase services using the commands and APIs it offers.

Use Cases

This server is suitable for AI applications that need to integrate with Firebase services, such as user authentication, data storage, and file management. It is particularly suitable for developers who want to quickly implement functions for interacting with Firebase.

Main Features

Firebase Authentication Integration
Supports verifying Firebase ID tokens, creating custom authentication tokens, and retrieving and deleting user information.
Firestore Database Operations
Provides functions for listing collections, creating, retrieving, updating, and deleting documents, as well as queries with filtering conditions.
Cloud Storage Management
Supports file upload, download, deletion, and listing, facilitating the handling of files in cloud storage.
State Management
Supports saving in Redis or memory for maintaining session states and persisting data.
Easy Integration
Can be easily integrated into existing Django projects and provides an independent test mode for the agent.
Advantages
Provides a standard protocol for easy interaction between AI agents and Firebase services
Supports multiple Firebase functions, including authentication, database, and storage
Easy to integrate into existing projects, suitable for rapid development
Supports state management to ensure session persistence
Limitations
Requires a Firebase project and relevant credentials, and the initial setup is relatively complex
May require a certain learning curve for non-technical users
Requires additional deployment and maintenance when relying on Redis

How to Use

Clone the Project
Clone the code repository of the Django Firebase MCP server from GitHub.
Install Dependencies
Install the required Python packages in the project directory.
Configure Firebase
Create a project in the Firebase console and obtain the service account key file. Save it as credentials.json.
Set Environment Variables
Create a .env file and fill in the configuration information related to Firebase and MCP.
Start the Server
Run the Django development server to start the MCP service.

Usage Examples

Interaction between AI Agent and Firebase Database
An AI agent interacts with the Firebase Firestore database through the MCP protocol to perform data query and update operations.
File Upload and Management
An AI agent uses the MCP protocol to upload and manage files in cloud storage.

Frequently Asked Questions

How to solve the error that the default app does not exist?
What if the server fails to start?
What if the Firebase connection fails?
How to switch to Redis state management?

Related Resources

Firebase Official Documentation
The official documentation of Firebase, providing detailed service descriptions and usage guides.
Django Official Documentation
The official documentation of Django, providing comprehensive information about the Django framework.
GitHub Project Repository
The GitHub project repository of the Django Firebase MCP server.
MCP Protocol Specification
The detailed specification document of the Model Context Protocol (MCP).

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

R
Rsdoctor
Rsdoctor is a build analysis tool specifically designed for the Rspack ecosystem, fully compatible with webpack. It provides visual build analysis, multi - dimensional performance diagnosis, and intelligent optimization suggestions to help developers improve build efficiency and engineering quality.
TypeScript
6.7K
5 points
N
Next Devtools MCP
The Next.js development tools MCP server provides Next.js development tools and utilities for AI programming assistants such as Claude and Cursor, including runtime diagnostics, development automation, and document access functions.
TypeScript
7.4K
5 points
T
Testkube
Testkube is a test orchestration and execution framework for cloud-native applications, providing a unified platform to define, run, and analyze tests. It supports existing testing tools and Kubernetes infrastructure.
Go
4.1K
5 points
M
MCP Windbg
An MCP server that integrates AI models with WinDbg/CDB for analyzing Windows crash dump files and remote debugging, supporting natural language interaction to execute debugging commands.
Python
7.7K
5 points
R
Runno
Runno is a collection of JavaScript toolkits for securely running code in multiple programming languages in environments such as browsers and Node.js. It achieves sandboxed execution through WebAssembly and WASI, supports languages such as Python, Ruby, JavaScript, SQLite, C/C++, and provides integration methods such as web components and MCP servers.
TypeScript
4.9K
5 points
N
Netdata
Netdata is an open-source real-time infrastructure monitoring platform that provides second-level metric collection, visualization, machine learning-driven anomaly detection, and automated alerts. It can achieve full-stack monitoring without complex configuration.
Go
6.5K
5 points
M
MCP Server
The Mapbox MCP Server is a model context protocol server implemented in Node.js, providing AI applications with access to Mapbox geospatial APIs, including functions such as geocoding, point - of - interest search, route planning, isochrone analysis, and static map generation.
TypeScript
6.7K
4 points
U
Uniprof
Uniprof is a tool that simplifies CPU performance analysis. It supports multiple programming languages and runtimes, does not require code modification or additional dependencies, and can perform one-click performance profiling and hotspot analysis through Docker containers or the host mode.
TypeScript
7.6K
4.5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
18.7K
4.5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
19.3K
4.3 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
59.0K
4.3 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
28.8K
5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
25.2K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
54.8K
4.5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
38.7K
4.8 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
17.6K
4.5 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase