wavekit-mcp
An MCP server that provides AI assistants with a persistent, sandboxed Python environment for waveform analysis, enabling loading and manipulation of VCD/FST/FSDB files and temporal pattern matching.
README
wavekit-mcp
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An MCP server that gives AI assistants a persistent, sandboxed Python environment for waveform analysis using wavekit.
The AI can open VCD/FST/FSDB files, load and manipulate waveforms, run temporal pattern matching, and iterate across multiple tool calls — all within a shared execution context that persists state between calls.
Why wavekit-mcp?
The problem: Digital waveforms are huge. A single simulation can produce millions of transitions across thousands of signals. Sending this data to an LLM directly is both inefficient and ineffective — the AI sees noise, not insight.
Our approach: Give the AI tools, not data. wavekit-mcp exposes wavekit's full waveform analysis capabilities through a persistent Python session. The AI writes code to:
- Load signals from VCD/FST/FSDB files
- Apply temporal pattern matching
- Compute statistics, detect anomalies, extract events
The AI gets only the answers it asks for — a mean, a timing violation, a filtered subset — never the raw waveform. Output limits ensure the AI must think in terms of signal semantics, not value sequences.
Installation
pip install wavekit-mcp
Start the server:
wavekit-mcp # defaults
wavekit-mcp --config wavekit_mcp.toml # custom config
Register with your MCP client (e.g. Claude Desktop):
{
"mcpServers": {
"wavekit": {
"command": "wavekit-mcp",
"args": ["--config", "/path/to/wavekit_mcp.toml"]
}
}
}
Configuration
Copy wavekit_mcp.toml.example and edit as needed. All fields are optional.
[limits]
max_sessions = 5
run_timeout_sec = 120
output_max_chars = 500
result_preview_items = 30
[file_access]
read_enabled = false
write_enabled = false
read_allowed_paths = ["/tmp/**"]
write_allowed_paths = ["/tmp/**"]
[log]
file = "/var/log/wavekit_mcp.log" # empty = stderr only
level = "INFO" # DEBUG logs full code + result per run
Scalar fields can be overridden via environment variable:
WAVEKIT_MCP_RUN_TIMEOUT_SEC=300 wavekit-mcp
Tools
| Tool | Description |
|---|---|
open_session(description?) |
Create a session; returns session_id |
close_session(sid) |
Release all resources |
list_sessions() |
List all active sessions with id, description, created_at |
run(sid, code) |
Execute Python; returns {result, output, error, duration_ms} |
get_history(sid, n) |
Last N execution records |
get_api_docs(topic) |
wavekit API reference |
Every session has these pre-injected: wavekit, Pattern, Channel, VcdReader, FstReader, FsdbReader, Viewer.
Use wavekit.MatchStatus, wavekit.Waveform, etc. for other types.
numpy is available via default allowed_imports: import numpy as np.
run() returns structured summaries for large objects rather than raw data — the Waveform, ndarray, and MatchResult objects stay in the session namespace for further processing.
Usage Examples
Load and analyse
# call 1
r = VcdReader("/data/sim.vcd")
data = r.load_waveform("tb.dut.data[7:0]", clock="tb.clk")
# call 2 — state persists
print(f"samples={len(data.value)}")
Pattern matching (AXI read latency)
arvalid = r.load_waveform("tb.arvalid", clock="tb.clk")
arready = r.load_waveform("tb.arready", clock="tb.clk")
rvalid = r.load_waveform("tb.rvalid", clock="tb.clk")
rready = r.load_waveform("tb.rready", clock="tb.clk")
result = (
Pattern()
.wait(arvalid & arready)
.wait(rvalid & rready)
.timeout(256)
.match()
)
valid = result.filter_valid()
print(f"transactions={len(valid.duration.value)} mean={np.mean(valid.duration.value):.1f} cycles")
Security
Code runs under RestrictedPython: import is blocked by default, __class__ / __bases__ access is blocked, and file I/O is disabled by default. Designed to prevent accidental operations, not to sandbox fully untrusted code.
Relaxing restrictions
To allow specific imports, add to your config:
[sandbox]
allowed_imports = ["plotly.*", "matplotlib.*"] # glob patterns
# allowed_imports = ["*"] # allow all imports
AI assistant skill
This repository includes a Claude/OpenCode skill for wavekit-mcp usage:
- skills/wavekit-usage/SKILL.md — installable skill entry point
- skills/wavekit-usage/references/cheatsheet.md — detailed cheatsheet of common patterns
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