re-llm-decompile
MCP server that exposes an AI decompiler via an OpenAI-compatible API, enabling decompilation, explanation, and variable renaming of disassembly for binary analysis.
README
re-llm-decompile
MCP server that exposes an AI decompiler via the OpenAI-compatible /v1/chat/completions API. Works with:
- LLM4Decompile (the
EndorRefvariants, or the latest SK²Decompile) served via vLLM - Ollama running any code model (CodeLlama, DeepSeek-Coder, Qwen2.5-Coder, etc.)
- Any other OpenAI-compatible endpoint
The server does not read files itself. The caller (Claude Code) is expected to obtain the disassembly with re-rizin.disassemble_function and pass it in. The server's job is to take the disassembly, optionally the raw bytes, and produce C-like pseudocode.
Tools
| Tool | What it does |
|---|---|
check_endpoint |
Hit /v1/models, return the list of available models |
decompile_function |
Send disassembly to the LLM, return C-like pseudocode |
explain_function |
Have the LLM explain disassembly (no rewrite) |
rename_variables |
Have the LLM propose better names for compiler-generated symbols |
summarize_binary |
Whole-binary summary from strings + imports + entry-point disasm |
Configuration
| Env var | Default | Purpose |
|---|---|---|
LLM_DECOMPILE_ENDPOINT |
http://localhost:11434/v1 |
OpenAI-compatible base URL |
LLM_DECOMPILE_MODEL |
llm4decompile |
Model name to request |
LLM_DECOMPILE_API_KEY |
(empty) | API key (use sk-... for OpenAI; empty for Ollama) |
Install
This server is part of the RE-AI plugin. The plugin's install.sh / install.bat installs it as part of the standard flow.
To install standalone:
pip install -e ./servers/re-llm-decompile
Run
re-llm-decompile # stdio transport (default for MCP)
python -m re_llm_decompile # equivalent
Usage pattern (in Claude Code)
1. "Decompile main in /bin/ls"
2. Claude calls re-rizin.analyze_function → function list
3. Claude calls re-rizin.disassemble_function(name="main") → asm
4. Claude calls re-llm-decompile.decompile_function(asm=..., arch="x86_64")
5. Claude returns the C-like pseudocode to the user
Choosing a model
- LLM4Decompile 22B (Ref): best quality for Linux x86_64 binaries, requires ~44GB VRAM (or AWQ/GPTQ quantizations).
- LLM4Decompile 6.7B (Ref): a good middle ground, ~14GB VRAM.
- Ollama + Qwen2.5-Coder 7B: reasonable general-purpose code model. Quality is lower than LLM4Decompile for pure binary decompilation but it explains disassembly well.
- Claude / GPT (via this server): not recommended — the prompt is tuned for open decompilation models. If you want to use Claude, call it directly through Claude Code rather than going through this server.
Deprecation note
The v1 re-ai repo did not have this server — it tried to decompile with pefile+capstone+llm prompts in its own agent loop. That is exactly the kind of thing Claude Code is good at. This server exists to give Claude Code a clean decompilation handle.
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