LPC MCP Server

Bring LPC development into 2025 with AI-powered code intelligence.

This MCP (Model Context Protocol) server wraps the jlchmura/lpc-language-server and exposes it to AI assistants, enabling natural language queries about your LPC codebase with real language server-powered understanding.

What This Enables

AI assistants can now:

• Understand your LPC code structure through the language server
• Get real documentation from hover information
• Jump to definitions and find references
• Answer natural language questions about your mudlib
• Trace inheritance chains and function calls
• Explain complex code patterns

All through conversation, powered by actual code intelligence instead of pattern matching.

Features

• lpc_hover: Get documentation/hover information for symbols
• lpc_definition: Jump to definition of symbols
• lpc_references: Find all references to a symbol
• lpc_diagnostics: Get real-time errors, warnings, and hints from the language server
• Workspace-aware: Reads your lpc-config.json for proper symbol resolution
• Fast: Direct JSON-RPC communication with the language server

Prerequisites

1. Install Node.js

Node.js 20+ required:

node --version  # Should be v20.0.0 or higher

2. Install the LPC Language Server Extension

The extension must be installed in VS Code (the server binary is bundled with it):

code --install-extension jlchmura.lpc

Verify installation:

ls ~/.vscode/extensions/jlchmura.lpc-*/out/server/src/server.js

3. Install Dependencies

cd /path/to/lpc-mcp
npm install

4. Create lpc-config.json in Your Mudlib

The language server needs this config file at your mudlib root to understand includes, simul_efuns, etc.

Example /path/to/your/mudlib/lpc-config.json:

{
  "driver": {
    "type": "fluffos"
  },
  "libFiles": {
    "master": "adm/obj/master.c",
    "simul_efun": "adm/obj/simul_efun.c",
    "global_include": "include/global.h"
  },
  "libInclude": [
    "include",
    "include/driver",
    "adm/include"
  ],
  "exclude": [
    ".git/",
    "tmp/"
  ]
}

Setup for Different AI Tools

Warp (Terminal)

Add to your Warp MCP configuration:

Location: Settings → AI → Model Context Protocol

{
  "lpc": {
    "command": "node",
    "args": ["/absolute/path/to/lpc-mcp/index.js"],
    "env": {
      "LPC_WORKSPACE_ROOT": "/path/to/your/mudlib"
    }
  }
}

Important: Use absolute paths! Replace:

• /absolute/path/to/lpc-mcp/index.js with the actual path to this repo
• /path/to/your/mudlib with the directory containing your lpc-config.json

Restart Warp after adding the configuration.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or equivalent:

{
  "mcpServers": {
    "lpc": {
      "command": "node",
      "args": ["/absolute/path/to/lpc-mcp/index.js"],
      "env": {
        "LPC_WORKSPACE_ROOT": "/path/to/your/mudlib"
      }
    }
  }
}

Restart Claude Desktop after configuration.

Cline (VS Code Extension)

Add to your Cline MCP settings:

{
  "mcpServers": {
    "lpc": {
      "command": "node",
      "args": ["/absolute/path/to/lpc-mcp/index.js"],
      "env": {
        "LPC_WORKSPACE_ROOT": "/path/to/your/mudlib"
      }
    }
  }
}

GitHub Copilot (VS Code)

Prerequisites:

• Install the Copilot MCP extension: code --install-extension automatalabs.copilot-mcp

Configuration: Add to ~/Library/Application Support/Code/User/mcp.json (macOS) or equivalent:

{
  "servers": {
    "lpc": {
      "type": "node",
      "command": "node",
      "args": ["/absolute/path/to/lpc-mcp/index.js"],
      "env": {
        "LPC_WORKSPACE_ROOT": "/path/to/your/mudlib"
      }
    }
  },
  "inputs": []
}

Other MCP-Compatible Tools

The configuration is the same for any MCP-compatible tool:

1. Add the server to your MCP configuration
2. Provide the Node.js command and path to index.js
3. Set LPC_WORKSPACE_ROOT environment variable to your mudlib root

Usage Examples

Once configured, you can ask your AI assistant natural language questions:

"What does the query_short() function do in room.c?" → AI uses lpc_hover to get documentation

"Where is STD_OBJECT defined?" → AI uses lpc_definition to find the file

"Find all places that call set_room_size()" → AI uses lpc_references to locate all callers

"Explain how the maze generation algorithm works" → AI reads code and uses hover info to understand functions

"What's the inheritance tree for rooms?" → AI traces inherit statements and jumps to definitions

"Check if this LPC file has any syntax errors" → AI uses lpc_diagnostics to validate the code

"Why won't this LPC code compile?" → AI checks diagnostics for errors like undeclared variables or type mismatches

Testing

To verify the server works:

# Set workspace root for testing
export LPC_WORKSPACE_ROOT=/path/to/your/mudlib

# Start the server (it will wait for MCP protocol messages)
node index.js

The server should output:

Starting LPC Language Server...
Initializing LSP...
LPC Language Server started successfully
LPC MCP Server running on stdio

Troubleshooting

Server won't start

Check the LPC extension is installed:

code --list-extensions | grep jlchmura.lpc

Check logs (for Warp):

tail -f ~/.local/state/warp-terminal/mcp/*.log

Language server not resolving symbols

Verify workspace root:

• Make sure LPC_WORKSPACE_ROOT points to the directory with lpc-config.json
• Use absolute paths, not relative

Check your lpc-config.json:

cat $LPC_WORKSPACE_ROOT/lpc-config.json

Extension version mismatch

If the extension path doesn't match, update line 40 in index.js:

const lspPath = path.join(
  process.env.HOME,
  ".vscode/extensions/jlchmura.lpc-VERSION/out/server/src/server.js"
);

Find your version:

ls ~/.vscode/extensions/ | grep jlchmura.lpc

How It Works

AI Assistant
    ↓ (natural language)
  MCP Protocol
    ↓ (tool calls: lpc_hover, lpc_definition, lpc_references)
  This Server
    ↓ (JSON-RPC: textDocument/hover, etc.)
  LPC Language Server
    ↓ (parses LPC, reads lpc-config.json)
  Your Mudlib

1. AI assistant sends MCP tool requests
2. Server reads the file and sends textDocument/didOpen to LSP
3. Server translates MCP → LSP JSON-RPC requests
4. LSP analyzes code using your lpc-config.json
5. Server returns LSP response as MCP result
6. AI understands your code structure!

Roadmap

• Add completion support
• Add diagnostics (errors/warnings)
• Support signature help
• Cache opened documents
• Support multiple workspace roots
• Add rename symbol support
• Add document symbols (outline)
• Add workspace symbol search

Contributing

PRs welcome! This is a proof-of-concept that can be extended with more LSP features.

Credits

• John (jlchmura) - The INCOMPARABLY SKILLED MASTER PROGRAMMER whose LPC language server rescued LPC development from 1995. Without his greatness, kindness, and all-around hunk demeanour, we would still be grep-ing through mudlibs like cavemen. This MCP server is merely a humble wrapper around his genius.
• Model Context Protocol - The protocol making this possible
• Built in an hour of inspired hacking in 2025

License

Unlicense - Public Domain. Do whatever you want with this code.

Note

The LPC language server itself (jlchmura/lpc-language-server) is under its own license.