Agentify Components
A

Agentify Components

Agentify Components is a framework for adding semantic metadata to React components, enabling AI systems and automation tools to understand component functions. It adds standardized descriptions to components through decorators and generates MCP server configurations to enable interaction between components and AI models.
2.5 points
6.7K

What is Model Context Protocol (MCP)?

Model Context Protocol (MCP) is an open standard for connecting AI models with external data sources and tools. Through a client - server architecture, it allows AI assistants to access real - time data (such as Google Drive, Slack, or databases), thereby enhancing their responsiveness and providing up - to - date context information.

How to use the MCP server?

Add semantic metadata to React components through the Agentify framework and generate a standardized MCP server. This enables AI systems to better understand and interact with your application.

Use cases

The MCP server is well - suited for applications that require deep integration with AI systems, such as customer service chatbots and automated process management tools.

Key Features

Support for multiple component types
Supports various React components, including search bars, forms, and buttons.
Generate standardized protocol
Convert component metadata into a format that complies with the MCP standard to ensure cross - platform compatibility.
Flexible expansion
Supports future expansion to other protocols to meet more business needs.
Advantages
Simplify the integration process of AI and web applications.
Improve the context awareness of AI systems.
Unified data connection method reduces redundant development work.
Limitations
Requires a certain technical background for setup and maintenance.
Currently only supports the definition of API and navigation behaviors.

How to Use

Install dependencies
Run the following command to install the Agentify Components package: `npm install @anvos/agentify - components`.
Define components
Use the `@AgentConfig` decorator on React components to add metadata.
Generate the MCP server
Create a `generate.ts` file and call the `generateMCPServer` function.
Deploy the server
Add scripts to `package.json` and execute the generation command.

Usage Examples

Search bar example
Add behavior descriptions to the search box so that AI can recognize its purpose.
Form submission example
Define the behavior and fields of the login form to facilitate AI understanding of its function.

Frequently Asked Questions

Does the MCP server support custom protocols?
How to verify that the generated MCP server is working properly?
Can the MCP server be used in an existing project?

Related Resources

Official Documentation
Get detailed setup guides and technical documentation.
GitHub Code Repository
View the source code and contribute to the project.
Product Requirements Document
Understand the full specifications and roadmap of the project.

Installation

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

Alternatives

V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
6.9K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
6.9K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
5.9K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
6.7K
4 points
P
Paperbanana
Python
8.2K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
7.3K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
7.9K
5 points
A
Apify MCP Server
The Apify MCP Server is a tool based on the Model Context Protocol (MCP) that allows AI assistants to extract data from websites such as social media, search engines, and e-commerce through thousands of ready-to-use crawlers, scrapers, and automation tools (Apify Actors). It supports OAuth and Skyfire proxy payment and can be integrated into MCP clients such as Claude and VS Code through HTTPS endpoints or local stdio.
TypeScript
7.0K
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
22.3K
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
25.4K
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
74.0K
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
36.5K
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#
32.5K
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
66.3K
4.5 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
21.6K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
99.0K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase