GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
MCP tools for UVM/cocotb logs, coverage, regressions, and waveform triage.
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。
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。
选择你使用的 AI 应用,然后复制设置。
SENTINEL_DV_CONFIG你需要
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": {
"sentinel-dv": {
"command": "uvx",
"args": [
"sentinel-dv",
"sentinel-dv-server"
],
"env": {
"SENTINEL_DV_CONFIG": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add sentinel-dv --env SENTINEL_DV_CONFIG=your-value -- uvx sentinel-dv sentinel-dv-server运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"sentinel-dv": {
"command": "uvx",
"args": [
"sentinel-dv",
"sentinel-dv-server"
],
"env": {
"SENTINEL_DV_CONFIG": "your-value"
}
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"sentinel-dv": {
"type": "stdio",
"command": "uvx",
"args": [
"sentinel-dv",
"sentinel-dv-server"
],
"env": {
"SENTINEL_DV_CONFIG": "your-value"
}
}
}
}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。
SENTINEL_DV_CONFIG env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。
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10日
注册名称已通过 GitHub 账户 kiranreddi 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
GitHub 仓库最后更新于–,最新版本(2.3.1)于3个月前进入注册中心。
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)。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
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。
Sentinel DV v2.3.1 is a read-only Model Context Protocol server for design verification evidence. It indexes exported SystemVerilog, UVM, cocotb, assertion, coverage, regression, and waveform artifacts into DuckDB and exposes 28 bounded, schema-driven tools to AI agents.
Documentation | Quick start | Video walkthrough | All tools | Agent skills
*.wave.json and bounded VCD summaries. Native FSDB/WLF streaming is intentionally out of scope.Sentinel DV does not execute simulations, modify RTL or testbench files, or stream unrestricted raw artifacts. runs.submit and tests.replay return dry-run commands for engineer review.
Python 3.10 or newer is required. This example indexes the checked-in demo corpus:
For a persistent environment, install sentinel-dv>=2.3.1. The commands below use uvx to run the same release without a persistent install.
git clone https://github.com/kiranreddi/sentinel-dv.git
cd sentinel-dv cp demo/config.example.yaml demo/config.yaml
uvx --from sentinel-dv@2.3.1 \ sentinel-dv-index --config "$PWD/demo/config.yaml" --index-all
Connect one agent:
codex mcp add sentinel-dv \
--env SENTINEL_DV_CONFIG="$PWD/demo/config.yaml" \ -- uvx --from sentinel-dv@2.3.1 sentinel-dv-server
claude mcp add \
--env SENTINEL_DV_CONFIG="$PWD/demo/config.yaml" \ --transport stdio --scope local sentinel-dv \ -- uvx --from sentinel-dv@2.3.1 sentinel-dv-server
copilot mcp add sentinel-dv \
--env SENTINEL_DV_CONFIG="$PWD/demo/config.yaml" \ -- uvx --from sentinel-dv@2.3.1 sentinel-dv-server
Use an absolute SENTINEL_DV_CONFIG path. Verify the connection in the client's MCP status view, then call runs.list.
See Agent setup for configuration-file examples, project scope, skill discovery, and troubleshooting.
Copy config.example.yaml and define allowed artifact roots:
artifact_roots:
index: type: duckdb path: ./sentinel_dv.db
adapters: uvm: true cocotb: true assertions: true coverage: true waveform_summary: true
security: max_response_bytes: 2097152 max_page_size: 200 max_evidence_refs: 10
redaction: enabled: true redact_emails: true redact_paths: true
Build the index before starting the server:
sentinel-dv-index --config /absolute/path/to/config.yaml --index-all
sentinel-dv-server --config /absolute/path/to/config.yaml
Relative paths inside the YAML are resolved from the config file's directory. Production startup never silently falls back to demo data.
The 28 tools are grouped by engineering purpose:
| Area | Tools |
|---|---|
| Runs | runs.list, runs.get, runs.summary, runs.diff, runs.cross_sim, runs.submit |
| Tests | tests.list, tests.get, tests.history, tests.topology, tests.cluster, tests.replay |
| Failures and assertions | failures.list, assertions.list, assertions.get, assertions.failures, assertions.sva_status, assertions.vacuity |
| Coverage | coverage.list, coverage.summary, coverage.gaps, coverage.trend, coverage.advisor |
| Regression and simulation | regressions.summary, regression.health, sim.status |
| Waveforms | wave.signals, wave.summary |
Every registered tool carries read-only MCP annotations and a versioned output schema. The MCP tools reference documents exact inputs and outputs.
The canonical skills live under skills/:
sentinel-dv-regression-triagesentinel-dv-failure-debuggingsentinel-dv-coverage-closureDeterministic mirrors support project discovery:
| Host | Path |
|---|---|
| Codex | .agents/skills/ |
| Claude Code | .claude/skills/ |
| GitHub Copilot | .github/skills/ |
The repository also contains Codex and Claude plugin manifests. .mcp.json defines the bundled stdio server command; provide SENTINEL_DV_CONFIG or a config.yaml in the server working directory.
After editing a canonical skill:
.venv/bin/python scripts/sync_agent_skills.py
.venv/bin/python scripts/sync_agent_skills.py --check
*.wave.json and VCDAdapter output is normalized into versioned schemas so clients do not need vendor-specific parsing logic.
Read Security and Production deployment before using production artifacts.
Create a development environment:
python3 -m venv .venv
.venv/bin/pip install -e ".[dev,docs]"
Run endpoint and workflow checks:
.venv/bin/python scripts/verify_all_mcp_tools.py
.venv/bin/python scripts/verify_skill_workflows.py
Run the full quality suite:
.venv/bin/pytest
.venv/bin/ruff check . .venv/bin/black --check . .venv/bin/mypy sentinel_dv .venv/bin/mkdocs build --strict
The all-tools verifier invokes every registered MCP endpoint. The skill verifier indexes 52 checked-in demo artifacts and executes the published regression triage, failure debugging, and coverage closure sequences.
sentinel_dv/
adapters/ artifact parsers indexing/ DuckDB indexing and queries normalization/ signatures, taxonomy, redaction, coverage guidance schemas/ versioned response contracts tools/core.py tool implementations server.py FastMCP registration and stdio entry point
skills/ canonical agent skills demo/ license-free exported verification fixtures docs/ MkDocs documentation scripts/ verification, gallery, release, and skill-sync tooling tests/ unit and integration coverage
See CONTRIBUTING.md. Sentinel DV is licensed under Apache-2.0.