Generic AI coding assistants are great at boilerplate but weak at FiveM specifics — they hallucinate native signatures, mix up framework APIs, and can't see your running server. The tools below close that gap. They're grouped by what they actually do, so you can pick what fits your workflow.
1. FiveM-aware documentation lookup
The single biggest accuracy win is giving your AI a reliable native and framework reference. Instead of guessing, the model looks up the exact signature of a native, the correct ESX/QBCore export, or an ox_lib helper. FiveClaw's fivem-mcp covers 6,400+ natives plus ESX, QBCore, ox_core, and ox_lib docs — free with any API key.
2. Code intelligence and review
Beyond lookups, code-intelligence tools analyze your actual resources: detecting anti-patterns (blocking loops, unguarded events), finding duplicate logic, mapping load order and dependencies, and reviewing diffs with FiveM context. This is where most production bugs get caught before they reach a live server.
3. Security scanning
FiveM resources are a common attack surface — SQL injection through unsanitized events, trusting client-side values, and exposed exports. An automated, per-resource security scanner flags these patterns so you fix them before a malicious player finds them.
4. Testing without a live server
Spinning up FXServer to test one function is slow. Tools that run Lua unit tests, simulate events, and exercise database logic without a running game server tighten the feedback loop dramatically — and make coverage measurable.
5. Live server access for your AI
The most powerful setup connects the AI directly to your server: searching every resource file, tailing FXServer logs in real time, running MySQL queries, and hot-restarting resources via txAdmin. FiveClaw's open-source local agent provides all of this for free.
How to choose
- Solo / hobby: start with free docs lookup and the local agent — that alone removes most hallucinations.
- Serious development: add code intelligence and security scanning to catch bugs and vulnerabilities pre-deploy.
- Teams / multiple servers: layer in a test engine, shared context memory, and multi-server management.