Discover and Install New Agent Capabilities
MCP Server connector for AI agents to discover and install new capabilities on demand, acting as an app store for agents.
Why it matters
Transform static language models into evolving agents by enabling them to discover and install new capabilities on demand, acting as an 'App Store for agents'.
Outcomes
What it gets done
Search the MCPfinder registry for available MCP servers by keywords or tags.
Retrieve detailed information about specific MCP servers.
Add or update MCP server configurations locally.
Remove MCP server configurations from local settings.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-mcpfinder | bash Capabilities
Tools your agent gets
Searches the MCPfinder registry for available MCP servers by keywords or tags
Retrieves detailed information about a specific MCP server, including its manifest and installation
Adds or updates MCP server configuration in the local configuration of the client application
Removes a specific MCP server configuration from the local configuration of the client application
Overview
MCPfinder MCP Server
What it does
MCPfinder enables language models to search for and install new MCP server capabilities on demand, acting as an "App Store for agents" that transforms static models into evolving agents that hunt for new capabilities.
How it connects
MCPfinder is useful for AI agents that need to discover and install new tools or functionalities they do not currently possess. This is ideal for scenarios where an AI needs to adapt to new tasks, such as discovering tools for code generation, data analysis, or specialized knowledge retrieval during a conversation. It can also be used to automatically expand AI capabilities in real-time.
Source README
MCPfinder enables language models to search for and install new MCP server capabilities on demand, acting as an "App Store for agents" that transforms static models into evolving agents that hunt for new capabilities.
Installation
Interactive Setup
npx -y @mcpfinder/server install
Cloud Access (HTTP/SSE)
claude mcp add --transport http mcpfinder https://mcpfinder.dev/mcp
From Source
git clone https://github.com/mcpfinder/server
node index.js
Configuration
Stdio Transport (Local)
{
"mcpServers": {
"mcpfinder": {
"command": "npx",
"args": [
"-y",
"@mcpfinder/server"
]
}
}
}
HTTP/SSE Transport (Cloud)
{
"mcpServers": {
"mcpfinder": {
"url": "https://mcpfinder.dev/mcp",
"transport": "http"
}
}
}
Available Tools
| Tool | Description |
|---|---|
search_mcp_servers |
Searches the MCPfinder registry for available MCP servers by keywords or tags |
get_mcp_server_details |
Retrieves detailed information about a specific MCP server, including its manifest and installation... |
add_mcp_server_config |
Adds or updates MCP server configuration in the local configuration of the client application... |
remove_mcp_server_config |
Removes a specific MCP server configuration from the local configuration of the client application... |
Features
- Effortless setup with instant availability
- AI-ready autonomous tool discovery and installation
- Real-time capability enhancement on demand
- Support for both stdio and HTTP/SSE transports
- Interactive setup tool for automatic MCP configuration
- Registry of verified MCP servers requiring no manual setup
- Server registration capability for publishers
- Support for both Node.js (npx) and Python (uvx) packages
Environment Variables
Optional
MCPFINDER_API_URL- Base URL for the MCPfinder registry APIMCP_PORT- Port number on which the server will listen in HTTP mode
Usage Examples
Search for MCP servers with the capabilities you need
Install new tools when AI lacks a required capability
Discover available MCP servers for code generation, data analysis, or specialized knowledge
Automatically expand AI capabilities during conversations
Notes
The registry contains several hundred servers that can be run locally using npx or uvx without needing to configure environment variables. The server acts as the primary interface for discovering and enabling new tools when requested capabilities are unavailable in the current set of MCP tools.
Discussion
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