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Sentinel DV

kiranreddi/sentinel-dv
2STDIOregistry active
Summary

Sentinel DV bridges AI agents to hardware verification artifacts through 28 read-only MCP tools covering UVM, cocotb, and SystemVerilog environments. It indexes simulator logs, assertion failures, coverage reports, and waveform summaries into a DuckDB store, then exposes structured queries for test results, failure signatures, regression diffs, and topology discovery. The server enforces path sandboxing, automatic redaction of credentials and IPs, and bounded output sizes. You'd reach for this when debugging silicon verification runs with an LLM, letting Claude query why a testbench failed or compare coverage across regression runs without giving it raw log access or simulator control. Requires a config file pointing to artifact roots and a one-time indexing pass before queries work.

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🛡️ Sentinel DV v2.3.0 - Verification Intelligence for AI Agents

Python PyPI MCP Registry License CI Documentation PRs Welcome Coverage

A security-first MCP server for verification intelligence (SystemVerilog/UVM/cocotb)

Features • Architecture • Quick Start • Documentation


🌟 What is Sentinel DV?

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.

Verification Ecosystems Supported

  • 🔧 UVM (Universal Verification Methodology) - Enterprise verification framework
  • 🐍 cocotb - Python-based verification with coroutines
  • 📊 SystemVerilog - Assertions, coverage, and native testbenches
  • 🌊 Waveform summaries - *.wave.json and *.vcd via built-in parsers (no raw FSDB/WLF streaming)

All through a unified, schema-driven interface with built-in security, redaction, and deterministic outputs.


🏗️ Architecture

Sentinel DV follows a strict separation of concerns with security-first principles:

sentinel_dv/
├── server.py              # MCP server entrypoint
├── config.py              # Security limits, feature flags, governance
├── registry.py            # Tool registration and versioning
├── schemas/               # Typed contracts for all data
│   ├── common.py         # EvidenceRef, RunRef, base types
│   ├── tests.py          # TestCase, TestTopology, UvmTopology
│   ├── failures.py       # FailureEvent, FailureSignature
│   ├── assertions.py     # AssertionInfo, AssertionFailure
│   ├── coverage.py       # CoverageSummary, CoverageMetric
│   ├── regressions.py    # RegressionSummary, RunDiff
│   └── versioning.py     # Schema version management
├── tools/                 # MCP tools (discovery + detail)
│   ├── runs.py           # runs.list, runs.diff
│   ├── tests.py          # tests.list, tests.get, tests.topology
│   ├── failures.py       # failures.list
│   ├── assertions.py     # assertions.list/get/failures
│   ├── coverage.py       # coverage.list/summary
│   ├── regressions.py    # regressions.summary
│   └── wave.py           # wave.summary, wave.signals
├── indexing/              # Artifact indexing and querying
│   ├── indexer.py        # Build normalized index from artifacts
│   ├── store.py          # DuckDB storage interface
│   └── query.py          # Filter/sort/pagination
├── adapters/              # Parse verification artifacts
│   ├── uvm_log.py        # UVM log parsing
│   ├── cocotb.py         # cocotb result parsing
│   ├── assertion_reports.py # Assertion report/log parsing
│   ├── coverage_reports.py  # Coverage summary parsing
│   ├── protocol_tags.py     # Protocol taxonomy hints (AXI/APB/AHB/...)
│   ├── waveform_summary.py  # Precomputed *.wave.json
│   └── vcd_summary.py       # VCD → bounded summary (Verilator, etc.)
├── normalization/         # Security and determinism
│   ├── signatures.py     # Stable failure signature hashing
│   ├── taxonomy.py       # Failure categorization
│   └── redaction.py      # Automatic secret/PII redaction
└── utils/                 # Common utilities
    ├── hashing.py
    ├── time.py
    └── bounded_text.py

Design Principles:

  • Read-only by default - No simulator control, no artifact modification
  • Schema-first - Every response conforms to typed contracts
  • Deterministic - Same input → same output (no LLM-generated fields)
  • Evidence-based - All facts traceable to source artifacts
  • Bounded and safe - Automatic redaction, size limits, path sandboxing

✨ Features

🔒 Security First

  • Read-only by design - No simulation triggers or artifact writes
  • Automatic redaction - Credentials, tokens, emails, IP addresses, paths
  • Path sandboxing - Only configured artifact roots accessible
  • Bounded outputs - Max response sizes, max evidence excerpts
  • Provenance tracking - Every fact includes optional source references

📊 Rich Verification Data

  • Test results - Status, duration, seed, simulator info, DUT config
  • UVM topology - Env/agent/driver/monitor/scoreboard hierarchy
  • Failure analysis - Categorized events (assertion/scoreboard/protocol/timeout)
  • Assertion intelligence - SVA definitions, runtime failures, intent mapping
  • Coverage metrics - Functional/code/assertion/toggle/FSM coverage
  • Regression analytics - Pass rates, failure signatures, run diffs
  • Interface bindings - Protocol mapping (AXI/AHB/APB/PCIe/USB)

⚡ Performance & Scale

  • Efficient indexing - DuckDB for fast filtering and aggregation
  • Smart pagination - Bounded result sets with stable sorting
  • Normalized storage - Deduplicated, hashed artifacts
  • Selective projection - Request only needed fields

🔌 Simulator Agnostic

  • Works with any simulator (Synopsys VCS, Cadence Xcelium, Mentor Questa, Verilator)
  • Adapter pattern - Ingest tool-specific formats, output unified schemas
  • Pre-computed summaries - No runtime dependency on EDA tools

📋 Schema-Driven Contracts

  • Versioned schemas - SemVer with compatibility guarantees
  • JSON Schema validation - Deterministic, testable
  • Stable tool APIs - Backwards-compatible evolution
  • Self-documenting - Schemas define the interface

🚀 Quick Start

PyPI: Use sentinel-dv>=2.3.0 for commercial simulator fixtures (VCS, Questa, Cadence), multi-project demos, 28 MCP tools (v2.0 submission/SVA/replay + v2.1 DV intelligence), assertion/coverage intelligence, and waveform indexing.

Install from MCP Registry

Install via uv (uvx) or your MCP client’s registry UI using server name io.github.kiranreddi/sentinel-dv.

Claude Desktop / MCP client (stdio):

{
  "mcpServers": {
    "sentinel-dv": {
      "command": "uvx",
      "args": [
        "--from",
        "sentinel-dv@2.3.0",
        "sentinel-dv-server",
        "--config",
        "/absolute/path/to/config.yaml"
      ]
    }
  }
}

Alternatively set SENTINEL_DV_CONFIG to your config path and omit --config.

Before querying: build the artifact index (required once per config):

uvx --from sentinel-dv@2.3.0 sentinel-dv-index --config /absolute/path/to/config.yaml --index-all

Installation

# Clone the repository
git clone https://github.com/kiranreddi/sentinel-dv.git
cd sentinel-dv

# Install with development dependencies
pip install -e ".[dev]"

# Or production install (requires >=2.3.0 for all 28 MCP tools)
pip install "sentinel-dv>=2.3.0"

Configuration

Required: copy config.example.yaml to config.yaml (or set SENTINEL_DV_CONFIG / pass --config). The server does not start without a config file and does not auto-use demo/.

Create a config.yaml:

# Artifact roots (read-only)
artifact_roots:
  - /path/to/verification/regressions
  - /path/to/uvm/logs

# Index storage
index:
  type: duckdb
  path: ./sentinel_dv.db

# Adapters (enable/disable)
adapters:
  uvm: true
  cocotb: true
  assertions: true
  coverage: true
  waveform_summary: true   # *.wave.json and *.vcd under artifact_roots

# Security & limits
security:
  max_response_bytes: 2097152  # 2MB
  max_page_size: 200
  max_evidence_refs: 10
  max_excerpt_length: 1024

# Redaction
redaction:
  enabled: true
  patterns:
    - AKIA.*           # AWS keys
    - ghp_.*           # GitHub tokens
    - Bearer\s+\S+     # Bearer tokens
  redact_emails: true
  redact_paths: true

Running the Server

# Start the MCP server
python -m sentinel_dv.server --config config.yaml

# Index artifacts (one-time or scheduled)
python -m sentinel_dv.indexing.indexer --config config.yaml --index-all

# Run with Claude Desktop
# Add to Claude config:
{
  "mcpServers": {
    "sentinel-dv": {
      "command": "python",
      "args": ["-m", "sentinel_dv.server", "--config", "/path/to/config.yaml"]
    }
  }
}

Example Queries

With Claude or any MCP client:

"Why did test axi_burst_test fail in the latest regression?"
→ Uses: tests.list, failures.list, tests.topology

"What assertions failed in the AXI agent?"
→ Uses: assertions.failures, assertions.get

"Compare coverage between runs R123 and R124"
→ Uses: runs.diff, coverage.summary

"Show me the failure signatures from the past week"
→ Uses: regressions.summary

📖 Documentation

Core Concepts

  • Architecture Overview - Design principles and structure
  • Schema Reference - Complete type definitions
  • Tool Contracts - Request/response specifications
  • Security Model - Redaction, bounding, sandboxing

Examples

  • Examples overview — VCS, Questa, Cadence, Verilator, cocotb, and UVM artifact fixtures
  • MCP tool gallery — SVG “screenshots” for all 28 tools
  • Verilator + VCD — Build, index, query wave.* with time windows
  • VCS, Questa, and Cadence — Exported artifact fixtures and all-tool verification
  • cocotb + waveforms — Index demo/ tree
  • demo/ — Runnable artifacts (multi-project UVM, cocotb, Verilator, VCS, Questa, Cadence)

Guides

  • Waveform summaries - JSON + VCD indexing
  • Getting Started - Setup and first queries
  • Adapter Development - Parse new artifact formats
  • Simulator Support - Vendor-specific notes
  • Deployment Guide - Production best practices

Reference

  • Documentation Site
  • Configuration Reference
  • Examples - Demo artifacts and clients

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for:

  • Code of Conduct
  • Development setup
  • Testing guidelines
  • Pull request process

Development

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run with coverage
pytest --cov=sentinel_dv --cov-report=html

# Lint and format
ruff check .
black .
mypy sentinel_dv/

📊 Project Status

  • ✅ Core schemas - Stable v1.0
  • ✅ MCP tools - 28 tools (discovery, analysis, regression, waveforms, v2.0 workflow, v2.1 DV intelligence, v2.3 run/test aggregation)
  • ✅ Adapters - UVM, cocotb, assertions, coverage
  • ✅ Indexing - DuckDB with efficient querying
  • ✅ Security - Redaction, sandboxing, bounding
  • ✅ Test coverage - 70%+ with unit and integration tests
  • ✅ Documentation - Full guides and API reference
  • ✅ Waveform summaries - *.wave.json + *.vcd (VcdSummaryParser); Verilator demo
  • ✅ Simulator examples - VCS, Questa, and Cadence exported artifact fixtures with all-tool verification
  • 🚧 Plugin ecosystem - Coming soon

🎯 Positioning

What Sentinel DV is

  • A read-only MCP server for verification ecosystems
  • A schema-first context provider for agents and LLMs
  • A deterministic translation layer from noisy artifacts to typed data
  • A composable infrastructure component for debug workflows

What Sentinel DV is not

  • ❌ It does not start simulations or submit jobs
  • ❌ It does not modify RTL/testbench code
  • ❌ It does not require any specific simulator
  • ❌ It is not an "AI that guesses"; it returns grounded, typed facts

🙏 Acknowledgments

Inspired by:

  • Sentinel CI - Universal CI/CD intelligence
  • Model Context Protocol - Anthropic's agent-context standard
  • The verification community using UVM, cocotb, and SystemVerilog

📄 License

Apache License 2.0 - see LICENSE for details.


🔗 Links

  • 🌐 Documentation
  • 💬 Discussions
  • 🐛 Issue Tracker
  • 📣 Changelog

Built with ❤️ for the verification community

⬆ back to top

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Configuration

SENTINEL_DV_CONFIG

Path to config.yaml (alternative to --config)

Categories
Security & Pentesting
Registryactive
Packagesentinel-dv
TransportSTDIO
UpdatedJun 1, 2026
View on GitHub

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