1mcpserver

# 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_search` tool 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](https://youtu.be/W4EAmaTTb2A) ## Quick Setup Choose **one** of the following: 1. **Remote** (simplest & fastest ⚡💨) 2. **Local (prebuilt)** — **Docker**, **uvx**, or **npx** 3. **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/](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` * **Codex**: * macOS: `~/.codex/config.toml` * Windows: `%USERPROFILE%\.codex\config.toml` **Remote config (JSON):** ```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: ```json { "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 🐳 > Use this if you want an isolated runtime and a single, reproducible command. ```bash docker run --rm -i \ -e DATADIR=/data \ -v "$PWD/db:/data" \ <YOUR_DOCKER_IMAGE_HERE> ``` ```json { "mcpServers": { "1mcpserver": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "DATADIR=/data", "-v", "${PWD}/db:/data", "<YOUR_DOCKER_IMAGE_HERE>" ] } } } ``` #### 2B) uvx 🐍 > Use this if you publish the server as a Python package and want a one-liner. ```bash uvx <YOUR_PACKAGE_NAME> --local ``` ```json { "mcpServers": { "1mcpserver": { "command": "uvx", "args": ["<YOUR_PACKAGE_NAME>", "--local"] } } } ``` #### 2C) npx 📦 > Use this if you publish a Node wrapper / launcher and want a one-liner. ```bash npx -y <YOUR_NPM_PACKAGE_NAME> ``` ```json { "mcpServers": { "1mcpserver": { "command": "npx", "args": ["-y", "<YOUR_NPM_PACKAGE_NAME>"] } } } ``` --- ### 3) Local (from source) 🧩 Clone this repo and run directly. ```bash git clone https://github.com/particlefuture/MCPDiscovery.git cd MCPDiscovery uv sync uv run server.py --local ``` ```json { "mcpServers": { "1mcpserver": { "command": "/path/to/uv", "args": [ "--directory", "<PATH_TO_CLONED_REPO>", "run", "server.py", "--local" ] } } } ``` > If your client supports remote `url` servers, 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: ```json { "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: 1. **Planning** — identify servers, keys, and config changes 2. **Testing** — verify servers (via `test_server_template_code`) 3. **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, npm, and uvx.  ## 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: * [https://mcpservers.org/](https://mcpservers.org/) * [https://glama.ai/mcp/servers](https://glama.ai/mcp/servers) ## Troubleshooting 🧰 * If using a venv and you get `ModuleNotFoundError` even after installing: delete the venv and recreate it.