Ai Agent Marketplace Index Search Mcp Server
MCP Server for AI Agent Marketplace Index from DeepNLP
Overview
What is the AI Agent Marketplace Index MCP?
The AI Agent Marketplace Index MCP is a server designed to help integrate and manage AI agents in a marketplace setting. This platform is based on DeepNLP principles, offering a strong framework for developers and businesses to efficiently deploy AI agents. The marketplace acts as a central hub for various AI solutions, allowing users to find, assess, and use AI agents that meet their specific needs.
Features of the AI Agent Marketplace Index MCP
- User-Friendly Interface: The platform provides an easy-to-use interface that makes navigation simple and improves user experience.
- Integration Capabilities: It integrates smoothly with existing systems and APIs, making it easy to deploy AI agents.
- Diverse AI Solutions: The marketplace hosts a wide variety of AI agents, serving different industries and applications.
- Real-Time Updates: Users receive real-time updates and notifications about new agents, features, and enhancements.
- Community Support: There is an active community of developers and users who contribute to the platform, share knowledge, and offer assistance.
How to Use the AI Agent Marketplace Index MCP
- Sign Up: Create an account on the platform to access all features and functionalities.
- Explore Agents: Browse the marketplace to discover various AI agents available for deployment.
- Integration: Follow the provided documentation to integrate selected AI agents into your existing systems.
- Customization: Tailor the AI agents to meet your specific requirements and preferences.
- Launch and Monitor: Deploy the AI agents and track their performance using the platform’s analytics tools.
Frequently Asked Questions
What types of AI agents can I find in the marketplace?
The marketplace includes a variety of AI agents, such as chatbots, data analysis tools, and automation agents, each designed for specific tasks and industries.
Is there a cost associated with using the AI Agent Marketplace Index MCP?
Some agents may be free, while others might require a subscription or one-time payment. Pricing details are usually available on the agent's page.
How can I contribute to the AI Agent Marketplace?
Developers can contribute by creating and submitting their own AI agents to the marketplace. Detailed guidelines for potential contributors are available on the platform.
What support options are available for users?
Users can access community forums, documentation, and customer support for help with any issues or questions related to the platform.
Can I track the performance of my deployed AI agents?
Yes, the platform offers analytics tools that enable users to monitor the performance and effectiveness of their deployed AI agents in real-time.
Details
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
- Clone this repository
- 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
Server Config
{
"mcpServers": {
"ai-agent-marketplace-index-mcp": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/metorial/mcp-container--ai-agent-hub--ai-agent-marketplace-index-mcp--ai-agent-marketplace-index-mcp",
"python main.py"
],
"env": {}
}
}
}