原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

TraceWeave

作者:gokeshenzhen版本 2.0.2i★ –i在你的电脑上运行
注册名称io.github.gokeshenzhen/traceweave

安装

概览

作者提供的说明(英文原文)

Portable MCP runtime for RTL logs and VCD; repository setup adds FSDB and site EDA integration

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "traceweave": {
      "command": "uvx",
      "args": [
        "traceweave-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add traceweave -- uvx traceweave-mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "traceweave": {
      "command": "uvx",
      "args": [
        "traceweave-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "traceweave": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "traceweave-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 gokeshenzhen 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 4906 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 4906 个服务器的 38% 更新
  • 基础检查结果等于或优于此分类中其他 4906 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

TraceWeave 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(2.0.2)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT4天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT16天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

🐙 TraceWeave

English · 简体中文

An MCP server for evidence-driven simulation debugging

TraceWeave is an MCP server for RTL / SoC debugging. It connects compile records, simulation logs, VCD/FSDB waveforms, and RTL source to your AI assistant, helping you work from a failed simulation to the relevant time, signals, and driving logic.

Use it with Claude Code, Codex, Copilot, or another MCP client. Describe the problem in natural language; the assistant uses tools to investigate, trace, and verify, with evidence you can review.

Use Cases · Installation · Client Setup · Start Debugging · Tool Quick Reference · FAQ · Documentation and Feedback

Use Cases

ProblemHow TraceWeave helps
A simulation times out or hangs, with no clear starting pointSummarize failures and scan interface handshakes to narrow down the affected interfaces and time window
A scoreboard mismatch or different results between runsCompare failure records and waveforms, locate observed differences, and trace data and control sources on both sides
A signal becomes X/ZFollow drivers and review waveform history to check whether a register sampled and retained an unknown value
Packed buses are hard to read, or TL-UL requests are not completingInspect address, data, and control fields individually, then check request/response handshakes, latency, and completion
Suspected ties, unconnected inputs, or magic-word conditionsStatically scan source code for constant connections, open inputs, and constant comparisons as investigation leads; no simulation run or waveform required
A deep SoC hierarchy with many modules and interfacesBrowse hierarchy on demand, locate instances and source files, and follow drivers, consumers, and connectivity paths
A debugging hypothesis needs evidenceSample by cycle and check timing conditions, handshake stability, and transaction completion

Supports VCS / Xcelium / Verilator simulation logs and VCD / FSDB / FST waveforms. Exported formal waveforms can also be queried; automatic artifact discovery currently supports JasperGold.

Optional FST support on Linux provides discovery, basic reads, fixed bit selections, expressions, cycle sampling, protocol and transaction analysis, cross-format comparison and X history. The summary lists the currently accepted tools.

Signal tracing (driver, load, and connectivity path queries) follows Verdi NPI → Source Graph → basic static analysis (Legacy Static) by default. It first queries the elaborated KDB; when NPI is unavailable or cannot provide a trustworthy result, it tries Source Graph without a commercial license, then falls back to basic static analysis where supported.

Source Graph counts independent structural writers separately from assignment statements. All retained branch evidence remains available; traversal reports writer, assignment inspection, and evidence limits separately. Overlapping writers are structural evidence, not proof of an observed value conflict. Bit provenance explicitly distinguishes found, proved_no_driver, and unknown, with reason codes and driver_set_complete. A budget or unsupported write never proves absence. If Static also cannot handle an inconclusive Source Graph query, the bounded Source Graph evidence and both attempts remain visible. Driver-chain and provenance rows share identical metadata within a writer; statement_evidence retains every source line and column. The legacy source_line names the first entry. query_instance_path names the queried instance, while resolved_instance_path keeps its historical head-driver meaning. VCD searches explain that direction=null means unavailable metadata.

Driver output migration: explain_signal_driver now defaults to traceweave.driver.compact.v1. Each response contains all retained evidence, with identical statement semantics and ordered locations/indices shared in typed evidence_tables. Legacy scripts should request output_format="full" to retain the original JSON shape and indentation, or decode the response:

from src.evidence_output import expand_compact_result

driver = expand_compact_result(text_content.text) print(driver["driver_chain"])

Reading only response["result"] does not expand its references. Table entries and location occurrences are not writer counts. Other tools keep their defaults and traceweave.compact.v1 contract. Distinct evidence can still produce large responses; this format does not guarantee inline delivery by every client.

Hierarchy handles live only in the server process. An explicit driver compile_context can recover a missing handle once under a 30-second, 4,096-source-file, 128-MiB read budget (stricter hierarchy settings apply). hierarchy_recovery reports reuse, rebuilding or a blocker. Supplied identity tokens are revalidated; without a historical source fingerprint, recovery establishes current sources only. Structural scanning remains a separate step.

Capabilities for large designs, with selected examples of validated scale:

  • Hierarchy and source browsing on demand: the server builds and retains hierarchy and file indexes, then returns local results by instance, subtree, or file to keep large SoC queries manageable in the assistant's context. Hierarchy construction and local queries have been verified on a synthetic design with 50,500 logical instances; the initial build still scans compilation records and sources.
  • Bulk handshake checks: sweep_handshakes discovers AHB / valid-ready interfaces and checks stalls, payload stability, and premature valid/HTRANS deassertion. A recorded design with 78,817 total signals and a 2.59 ms waveform yielded 49 candidate interfaces involving 262 clock/protocol signals; 35 interfaces were checked in about 4.65 minutes, with 14 skipped and partial coverage. Runtime and coverage depend on the waveform, interface types, and resource limits.
  • GiB-scale log parsing: parse_sim_log has been verified on a 1 GiB synthetic log with 2,097,152 lines, finding all four errors at the beginning, middle, and end.

Installation

Requires Python 3.11+. Choose the installation that fits your environment:

InstallationIntended use
RepositorySimulation hosts with an existing Verdi installation, for FSDB, Source Graph, and optional NPI / LSF
PyPILog and VCD analysis, or Source Graph without a commercial license
Repository Installation
git clone https://github.com/gokeshenzhen/TraceWeave.git

cd TraceWeave export VERDI_HOME=/path/to/verdi bash scripts/install.sh

The installer prepares the Python environment, Source Graph, and FSDB reader, then checks the runtime. It leaves shell startup files and MCP client configuration untouched. FSDB support builds against the Synopsys FSDB Reader SDK in VERDI_HOME; TraceWeave does not redistribute its headers or libraries. Use of the FSDB Reader is subject to the applicable VC Apps Access Program Agreement (or successor). NPI and KDB operations also require the appropriate EDA runtime and license from your site.

For an existing installation, start with a read-only check:

bash scripts/install.sh --check
PyPI Installation
python3.11 -m pip install "traceweave-mcp[source-graph]"

traceweave-mcp --doctor

For logs, VCD, and basic static analysis only, install traceweave-mcp without [source-graph]. The PyPI package does not include the FSDB reader; use the repository installation for FSDB.

Optional FST reads

Install the extra in the MCP server's Python environment: python3.11 -m pip install "traceweave-mcp[fst]". For a repository installation, use .venv/bin/python -m pip install "pylibfst==0.2.1". Reconnect the server, then check traceweave-mcp --doctor or get_sim_paths. Existing VCD/FSDB users do not need this dependency.

For example, ask: “Find the FST waveform under /path/to/run, show its summary, find top.data, and read its transitions from 10 ns to 20 ns.” The basic tools preserve X/Z and distinguish missing recording intervals from observed values. Nonzero time offsets, real/string signals, external hierarchy files, and whole-file gzip containers are currently unsupported. Reads exceeding the bounded index, native memory, result, or time limits stop explicitly; narrow the query or use a smaller dump. See FST boundaries and resource limits.

Use the same analysis tools to inspect FST handshakes, reconstruct transactions, compare an FST signal against VCD/FSDB, or trace an earlier X after its input has recovered. Source-based analysis keeps its usual compile-context prerequisites. Recording gaps and incomplete clock history remain partial evidence.

Client Setup

After a repository installation, generate a client configuration template with absolute paths:

ClientGenerate configuration template
Claude Codebash scripts/install.sh --print-config claude
Codexbash scripts/install.sh --print-config codex
Copilotbash scripts/install.sh --print-config copilot

These commands only print templates. Add the output to your client's MCP configuration, supply any required site EDA environment variables, and reconnect the server. See the client configuration reference for complete examples.

Other MCP clients supporting stdio can use these connection settings:

Installationcommandargs
Repository /.venv/bin/python[" /server.py"]
PyPItraceweave-mcp, or its absolute path[]
LSF-only NPI licenses

If Verdi/NPI licenses are available only on LSF compute nodes, provide these settings to the MCP server process. Replace digital with your queue:

export TRACEWEAVE_NPI_EXECUTION=lsf

export TRACEWEAVE_NPI_LSF_QUEUE="digital"

The client must inherit or explicitly pass these variables. Project files, the TraceWeave installation, and cache directories must be visible at the same absolute paths on submission and compute nodes. See the [LSF configuration reference](https://github.com/gokeshenzhen/TraceWeave/blob/main/docs/

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx