pqs-mcp-server

Install pqs-mcp-server in your MCP client

pqs-mcp-server is a Model Context Protocol server. Add it to your MCP client config once, restart, and the server's tools become available to your AI assistant. The same JSON snippet below works across all four major clients — only the config file path differs.

1. Locate your client's MCP config file.
   • Cursor: ~/.cursor/mcp.json
   • Claude Desktop (macOS): ~/Library/Application Support/Claude/claude_desktop_config.json
   • Claude Desktop (Windows): %APPDATA%\Claude\claude_desktop_config.json
   • VS Code: Settings → Extensions → MCP
   • Windsurf: Settings → MCP Servers
2. Add pqs-mcp-server to the mcpServers map — paste the snippet below into your config file. If you already have other MCP servers, merge the entry into the existing mcpServers object.
3. Restart your client so it picks up the new server.
4. Verify — ask the assistant to list available tools; pqs-mcp-server's tools should appear.

{
  "mcpServers": {
    "pqs-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "pqs-mcp-server"
      ],
      "env": {
        "PQS_API_KEY": "<your-pqs-api-key>"
      }
    }
  }
}

npm package: pqs-mcp-server

Required environment variables

pqs-mcp-server needs the following environment variables set before it can run. Add them to the env block of your mcpServers entry, or export them in your shell before launching the client.

• PQS_API_KEY

Transport

pqs-mcp-server supports the following MCP transports. Most AI clients use stdio by default for locally-installed servers.

More build.protocol_tooling.mcp MCP servers

Other Model Context Protocol servers in the same space as pqs-mcp-server. Each one adds different capabilities to your AI assistant — pick based on the data sources or workflows you need.

• infinitecampus-mcp

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• packet-tracer-mcp

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• opencut-controller

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Browse the full MCP server directory or use Stork's one-line install to let your agent pick the right server automatically.