keplertech/naja-scope

Let your AI assistant explore SystemVerilog and VHDL designs — without pasting source code into the chat.
naja-scope is an MCP server that gives AI
agents (Claude, and any MCP-compatible assistant) a precise, structured view of
your elaborated SystemVerilog or VHDL design. Instead of dumping thousands of lines of
RTL into the model's context, the agent asks targeted questions — what drives
this signal? what's inside this module? where does this net come from? — and
gets back small, exact answers with file-and-line references.
Built on the najaeda netlist engine.
> On a 17-question CVA6 benchmark,
> the same Claude Code agent scored 17/17 with naja-scope versus 10/17 with
> grep/read source tools — in 77 turns instead of 123, processing about 5×
> less input. How it was measured ↓
sh
pip install naja-scope
claude mcp add naja-scope -- naja-scope-mcp
## Why
Large designs don't fit in a chat window. Pasting RTL is slow, expensive, and
the model still can't reliably trace connectivity across hierarchy. naja-scope
turns your design into something an agent can navigate:
🔎 Trace connectivity — find what drives or loads any signal, across
module boundaries.
🌲 Walk the hierarchy — explore modules, instances, and ports on demand.
🎯 Jump to source — every answer comes with file:line ranges, so the
agent can quote the exact RTL that matters.
🧩 Logic cones — trace fan-in / fan-out combinational cones up to the
register boundary.
💡 Recover design intent — enum state names, struct/union fields, and
parameter formulas that normally vanish when a design is elaborated.
Requires najaeda 0.7.33 or newer, including the CVA6 RV32 elaboration
fix. See the
0.1.21 release notes
for test results and snapshot migration requirements.
Works on RTL and gate-level netlists alike: load elaborated SystemVerilog
or VHDL (beta), or load a post-synthesis structural Verilog netlist together with its Liberty
standard-cell library and navigate the gates the same way (see
Gate-level designs).
All responses are token-bounded: lists paginate, large results truncate with
clear markers. Your context stays small; your answers stay accurate.
## Does it actually help?
naja-scope helps most when the answer exists in the elaborated design rather
than in any single source file. In an initial 17-question run on the
cv32a6imacsv32 configuration of
CVA6, the same Claude Code agent was
tested with naja-scope and with source-search tools alone.
| Agent setup | Provider and models | Initial automated score | Turns | Input processed | Output tokens |
| Agent + naja-scope | Anthropic Claude Code; claude-sonnet-4-6 with claude-haiku-4-5-20251001 helper | 17 / 17 | 77 | 1,058,556 | 19,520 |
| Agent + grep/read source | Anthropic Claude Code; claude-sonnet-4-6 with claude-haiku-4-5-20251001 helper | 10 / 17 | 123 | 5,461,719 | 55,962 |
The difference is clearest on structural questions that source search cannot
answer directly:
| CVA6 question | Agent + naja-scope | Agent + grep/read source |
| Flattened register groups under exstagei | 92, in 4 turns | No answer at the turn limit |
| Flattened register groups under commitstagei | 0, in 3 turns | No answer at the turn limit |