Sentinel DV is an **open-source Model Context Protocol (MCP) server** that provides large language models and AI agents with **safe, structured, read-only access** to verification artifacts—enabling deterministic triage, root-cause analysis, and verification insight without exposing raw logs or granting control of simulators.
- ✓Open-source license (Apache-2.0)
- ✓Actively maintained (<30d)
- ✓Clear description
claude mcp add sentinel-dv -- uvx --from{
"mcpServers": {
"sentinel-dv": {
"command": "uvx",
"args": ["--from"]
}
}
}MCP Servers overview
# Sentinel DV <!-- mcp-name: io.github.kiranreddi/sentinel-dv --> [](https://pypi.org/project/sentinel-dv/) [](https://registry.modelcontextprotocol.io/?search=io.github.kiranreddi/sentinel-dv) [](https://github.com/kiranreddi/sentinel-dv/actions/workflows/ci.yml) [](https://github.com/kiranreddi/sentinel-dv/actions/workflows/docs.yml) [](LICENSE) 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](https://kiranreddi.github.io/sentinel-dv/) | [Quick start](docs/getting-started/quick-start.md) | [Video walkthrough](docs/getting-started/video-walkthrough.md) | [All tools](docs/tools/mcp-tools-reference.md) | [Agent skills](docs/skills/overview.md) ## What it provides - **Run and test intelligence:** discovery, summaries, history, topology, diffs, replay-command generation, and live-status snapshots. - **Failure analysis:** normalized categories, stable signatures, bounded evidence, assertion failures, and failure clustering. - **Coverage closure:** functional, code, toggle, and FSM metrics; trends; gaps; vacuity; SVA status; and protocol-aware constraint candidates. - **Waveform context:** precomputed `*.wave.json` and bounded VCD summaries. Native FSDB/WLF streaming is intentionally out of scope. - **Agent workflows:** regression triage, single-test failure debugging, and coverage closure skills for Codex, Claude Code, and GitHub Copilot. 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. ## Quick start 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. ```bash 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 "$PWD/demo/config.yaml" --index-all ``` Connect one agent: ### Codex ```bash codex mcp add sentinel-dv \ --env SENTINEL_DV_CONFIG="$PWD/demo/config.yaml" \ -- uvx --from sentinel-dv@2.3.1 sentinel-dv-server ``` ### Claude Code ```bash claude mcp add \ --env SENTINEL_DV_CONFIG="$PWD/demo/config.yaml" \ --transport stdio --scope local sentinel-dv \ -- uvx --from sentinel-dv@2.3.1 sentinel-dv-server ``` ### GitHub Copilot CLI ```bash copilot mcp add sentinel-dv \ --env SENTINEL_DV_CONFIG="$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](docs/getting-started/agent-setup.md) for configuration-file examples, project scope, skill discovery, and troubleshooting. ## Production configuration Copy `config.example.yaml` and define allowed artifact roots: ```yaml artifact_roots: - /absolute/path/to/regression/artifacts 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: ```bash 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. ## MCP tools 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](docs/tools/mcp-tools-reference.md) documents exact inputs and outputs. ## Agent skills The canonical skills live under `skills/`: - [`sentinel-dv-regression-triage`](skills/sentinel-dv-regression-triage/SKILL.md) - [`sentinel-dv-failure-debugging`](skills/sentinel-dv-failure-debugging/SKILL.md) - [`sentinel-dv-coverage-closure`](skills/sentinel-dv-coverage-closure/SKILL.md) Deterministic 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: ```bash .venv/bin/python scripts/sync_agent_skills.py .venv/bin/python scripts/sync_agent_skills.py --check ``` ## Supported artifact sources - UVM logs and topology hints - cocotb and generic JUnit XML - assertion definition and failure JSON - SVA run-status JSON - supported JSON, XML, text, and HTML coverage summaries - `*.wave.json` and VCD - live simulation status JSON - exported VCS, Xcelium, Questa, and Verilator results Adapter output is normalized into versioned schemas so clients do not need vendor-specific parsing logic. ## Security model - Tools are read-only and operate on an index plus configured artifact roots. - Path resolution is sandboxed to allowed roots. - Evidence counts, excerpts, pages, wave signals, bins, and total response size are bounded. - Configurable redaction protects common secrets, email addresses, IP addresses, and local paths. - Tool output is deterministic; the MCP server does not generate causal conclusions. Read [Security](docs/architecture/security.md) and [Production deployment](docs/deployment/production.md) before using production artifacts. ## Verification Create a development environment: ```bash python3 -m venv .venv .venv/bin/pip install -e ".[dev,docs]" ``` Run endpoint and workflow checks: ```bash .venv/bin/python scripts/verify_all_mcp_tools.py .venv/bin/python scripts/verify_skill_workflows.py ``` Run the full quality suite: ```bash .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. ## Project layout ```text 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 ``` ## Contributing See [CONTRIBUTING.md](CONTRIBUTING.md). Sentinel DV is licensed under [Apache-2.0](LICENSE).
What people ask about sentinel-dv
What is kiranreddi/sentinel-dv?
+
kiranreddi/sentinel-dv is mcp servers for the Claude AI ecosystem. Sentinel DV is an **open-source Model Context Protocol (MCP) server** that provides large language models and AI agents with **safe, structured, read-only access** to verification artifacts—enabling deterministic triage, root-cause analysis, and verification insight without exposing raw logs or granting control of simulators. It has 3 GitHub stars and was last updated today.
How do I install sentinel-dv?
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You can install sentinel-dv by cloning the repository (https://github.com/kiranreddi/sentinel-dv) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is kiranreddi/sentinel-dv safe to use?
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Our security agent has analyzed kiranreddi/sentinel-dv and assigned a Trust Score of 79/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.
Who maintains kiranreddi/sentinel-dv?
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kiranreddi/sentinel-dv is maintained by kiranreddi. The last recorded GitHub activity is from today, with 0 open issues.
Are there alternatives to sentinel-dv?
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Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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