AI Agent Marketplace Index

What is ai-agent-marketplace-index-mcp?

ai-agent-marketplace-index-mcp is an MCP (Multi-Cloud Platform) server developed by DeepNLP. It serves as a search engine and monitoring tool for the AI Agent Marketplace Index, which contains over 5000 AI agents and tools across various categories. It allows users to search for AI agents by keywords or categories and monitors their web traffic performance.

How to use ai-agent-marketplace-index-mcp?

To use ai-agent-marketplace-index-mcp, you need Python 3.10 or higher, a Microsoft Bing Search API key, and an MCP-compatible client like Claude Desktop or Cursor.

Installation:

1. Clone the repository.
2. Install dependencies using uv venv, source .venv/bin/activate, and uv pip install -e .

Running the server:

• Development: cd ./ai-agent-marketplace-index-mcp/src/ai-agent-marketplace-index then mcp dev server.py
• Production: uv run -m ai-agent-marketplace-index-mcp

Configuring with Claude for Desktop: Add the provided JSON configuration to your Claude Desktop configuration file, adjusting the absolute path to the project.

Available Tool:

• search_ai_agent(q: str, limit: int = 100, timeout: int = 5): General search of AI Agents for information, websites, content, and web traffic statistics.

Integrating with LLMs (e.g., Claude): Use the mcp_marketplace library to search for the MCP server and list its tools, then integrate these tools into your LLM's message creation process.

Key Features of ai-agent-marketplace-index-mcp

• Comprehensive AI Agent Search: Search for AI agents by query or category (e.g., "AI Coding", "HR AI Agents", "Finance AI Agent", "Healthcare AI Agent").
• AI Agent Web Traffic Monitoring: Monitor performance metrics such as Google/Bing ranking, GitHub Stars, and Arxiv References.
• API for Agent Listing: Provides an API to list new AI agents on the AI Agent Marketplace and Index.
• Robust Error Handling: Includes comprehensive error handling for reliable operation.
• MCP Marketplace Plugin Integration: Supports the MCP Marketplace Plugin for enhanced functionality.

Use Cases of ai-agent-marketplace-index-mcp

• Discovering AI Agents: AI assistants can use this server to find relevant AI agents, tools, or use cases by keywords or categories.
• Monitoring Agent Performance: Developers and users can monitor the web presence and popularity of various AI agents.
• Listing New Agents: AI agent developers can use the API to list their agents on the marketplace, increasing visibility.
• LLM Integration: Large Language Models can leverage the search_ai_agent tool to enhance their capabilities by finding and utilizing specific AI agents.

FAQ from ai-agent-marketplace-index-mcp

Q: What are the system requirements? A: Python 3.10 or higher, a Microsoft Bing Search API key, and an MCP-compatible client (e.g., Claude Desktop, Cursor).

Q: How can I integrate this with my LLM? A: You can use the mcp_marketplace library to search for the server and list its tools, then pass these tools to your LLM for selection and usage.

Q: Can I list my own AI agent on the marketplace? A: Yes, the project provides an API for listing your AI agents to the AI Agent Marketplace and Index.

AI Agent Marketplace Index Search MCP Server

MCP Server for AI Agent Marketplace Index from DeepNLP, , allowing AI assistants to searches available AI agents Navigation Page function, tools or use cases by "keywords" or "category". such as find all the "AI coding agents", "GUI AI Agents", "Mobile Use Agent", "Desktop Use Agent", etc.

Features

• Search AI Agents by query or category, find all available ai agents from the Agent Marketplace Index, such as "AI Coding", "HR AI Agents", "Finance AI Agent", "Healthcare AI Agent", "AI Agents Employees",etc.
• Monitor AI Agents Web Traffic Performance, such as Google/Bing ranking, Github Stars, Arxiv Reference.
• API to list your AI agents to the AI Agent Marketplace and Index
• Comprehensive error handling

Update

Add MCP Marketplace Plugin

Open Project https://github.com/AI-Agent-Hub/mcp-marketplace

Search Engine for AI Agents

Tool Listing

Tool Result

Requirements

• Python 3.10 or higher
• Microsoft Bing Search API key
• MCP-compatible client (e.g., Claude Desktop, Cursor)

Installation

1. Clone this repository
2. Install dependencies:

   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   uv pip install -e .
   

Configuration

Usage

Running the server

uv run -m ai-agent-marketplace-index-mcp

development

cd ./ai-agent-marketplace-index-mcp/src/ai-agent-marketplace-index
mcp dev server.py

Configuring with Claude for Desktop

Add the following to your Claude Desktop configuration file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
    "mcpServers": {
        "ai-agent-marketplace-index-mcp": {
            "command": "uv",
            "args": [
                "--directory",
                "/ABSOLUTE/PATH/TO/PARENT/FOLDER/ai-agent-marketplace-index-mcp/src/ai-agent-marketplace-index",
                "run",
                "server.py"
            ]
        }
    }
}

Available Tools

1. search_ai_agent

General search of AI Agents for information, websites, content and metric statistic of web traffic, etc.

search_ai_agent(q: str, limit: int = 100, timeout: int = 5)

Resources

MCP Marketplace API Support

• Allow any agent rag workflow to find this MCP Server via python/typescript API
• Search relevant servers by query/id/category
• Give LLM chances to choose this tools and enhance usage.

Example: Search Server and Tools

    import mcp_marketplace as mcpm
    mcpm.set_endpoint("deepnlp") # choose various open mcp marketplace endpoint

    result_q = mcpm.search(id="ai-agent-marketplace-index-mcp", mode="dict", page_id=0, count_per_page=100)
    result_id = mcpm.search(id="ai-agent-hub/ai-agent-marketplace-index-mcp", mode="dict", page_id=0, count_per_page=100)
    tools = mcpm.list_tools(id="ai-agent-hub/ai-agent-marketplace-index-mcp")

Example: Integrate with LLM e.g. Claude

    import anthropic
    client = anthropic.Anthropic()

    # Step 1. search mcp by query/id to find this mcp

    # Step 2. Calling LLM for Better Usage and MCP Selection
    response = client.messages.create(
        model="claude-3-7-sonnet-20250219", max_tokens=1024, tools=tools, messages=[]
    )
    print(response)
    ## install remote servers if tools from this mcp are chosen

License

MIT License