1 MCP Server 🚀
MCP of MCPs — automatically discover and configure MCP servers on your machine (remote or local).
After setup, you can usually just say:
“I want to perform . Call the
deep_searchtool and follow the outlined steps.”
The goal is that you only install this MCP server, and it handles the rest (searching servers, selecting servers, configuring servers, etc.).
Demo video 🎥: https://youtu.be/W4EAmaTTb2A
Quick Setup
Choose one of the following:
- Remote (simplest & fastest ⚡💨)
- Local (prebuilt) — Docker, uvx, or npx
- Local (from source) — run this repo directly
1) Remote 🌍⚡💨
Use the hosted endpoint (recommended for the simplest setup).
Docs + guided setup: https://mcp.1mcpserver.com/
Configure your MCP client
Add the following entry to your client config file:
- Cursor:
./.cursor/mcp.json - Gemini CLI:
./gemini/settings.json(see Gemini docs) - Claude Desktop:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
- Codex:
- macOS:
~/.codex/config.toml - Windows:
%USERPROFILE%\.codex\config.toml
- macOS:
Remote config (JSON):
{
"mcpServers": {
"1mcpserver": {
"url": "https://mcp.1mcpserver.com/mcp/",
"headers": {
"Accept": "text/event-stream",
"Cache-Control": "no-cache"
}
}
}
}
If you already have other servers configured, just merge this entry under mcpServers For example:
{
"mcpServers": {
"1mcpserver": {
"url": "https://mcp.1mcpserver.com/mcp/",
"headers": {
"Accept": "text/event-stream",
"Cache-Control": "no-cache"
}
},
"file-system": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-filesystem", "."]
}
}
}
Tip: If your client supports it, move the config file into your home directory to apply globally.
2) Local (prebuilt) 💻
Use this when you want everything local, or when your MCP client only supports STDIO.
2A) Docker 🐳
docker run -p 8080:8080 ghcr.io/particlefuture/1mcpserver:latest
Running on other host ports:
docker run -p <FREE_HOST_PORT_NUM>:8080 ghcr.io/particlefuture/1mcpserver:latest
Running with stdio instead of streamable-http (You might see some delays when trying to connect):
run --rm -i ghcr.io/particlefuture/1mcpserver:latest --local
{
"mcpServers": {
"1mcpserver": {
"url": "https://mcp.1mcpserver.com/mcp/"
}
}
}
2B) npx 📦
npx -y @1mcpserver/1mcpserver
3) Local (from source) 🧩
Clone this repo and run directly.
git clone https://github.com/particlefuture/MCPDiscovery.git
cd MCPDiscovery
uv sync
uv run server.py --local
{
"mcpServers": {
"1mcpserver": {
"command": "/path/to/uv",
"args": [
"--directory",
"<PATH_TO_CLONED_REPO>",
"run",
"server.py",
"--local"
]
}
}
}
If your client supports remote
urlservers, you can use the Remote setup instead.
Optional: grant file-system access 📁
If you want your LLM to have file-system access, add an MCP filesystem server and point it at the directory you want to allow:
{
"mcpServers": {
"file-system": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-filesystem", "~/"]
}
}
}
Architecture 🧠
There are two search modes:
Quick Search ⚡
For explicit requests like: “I want an MCP server that handles payments.”
Returns a shortlist of relevant MCP servers.
Deep Search 🌊
For higher-level or complex goals like: “Build a website that analyzes other websites.”
The LLM breaks the goal into components/steps, finds MCP servers for each part, and if something is missing, it asks whether to:
- ignore that part,
- break it down further, or
- implement it ourselves.
Deep Search stages:
- Planning — identify servers, keys, and config changes
- Testing — verify servers (via
test_server_template_code) - Acting — execute the workflow using the configured servers
Change Log 🕒
- July 31 2025: Upgrade to 0.2.0. Added agentic planning.
- Dec 12 2025: Support for Gemini + Codex
- Dec 13 2025: Easier local setup with docker and npm.
Future 🔮
- Better demo videos (new domain, narrated walkthrough)
- Model Context Communication Protocol (MCCP): standard server-to-server messaging
- Avoid calling tools with an
internal_prefix unless instructed - Improve MCP server database schema: server, description, url, config json, extra setup (docker/api key/etc)
Credits 🙏
Data sources:
- wong2/awesome-mcp-servers
- metorial/mcp-containers
- punkpeye/awesome-mcp-servers
- modelcontextprotocol/servers
Published to:
Troubleshooting 🧰
- If using a venv and you get
ModuleNotFoundErroreven after installing: delete the venv and recreate it.
Please create an issue or directly contact me zjia71@gatech.edu if you encounter ANY issue of frustration. I really hope the setup is as smooth as possible!!