io.github.kiranreddi/sentinel-dv
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@io.github.kiranreddi/sentinel-dvshow test failures from last regression run"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
π‘οΈ Sentinel DV v2.3.0 - Verification Intelligence for AI Agents
A security-first MCP server for verification intelligence (SystemVerilog/UVM/cocotb)
Features β’ Architecture β’ Quick Start β’ Documentation
π 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 artifactsβenabling deterministic triage, root-cause analysis, and verification insight without exposing raw logs or granting control of simulators.
Verification Ecosystems Supported
π§ UVM (Universal Verification Methodology) - Enterprise verification framework
π cocotb - Python-based verification with coroutines
π SystemVerilog - Assertions, coverage, and native testbenches
π Waveform summaries -
*.wave.jsonand*.vcdvia built-in parsers (no raw FSDB/WLF streaming)
All through a unified, schema-driven interface with built-in security, redaction, and deterministic outputs.
Related MCP server: Debugging MCP Server
ποΈ Architecture
Sentinel DV follows a strict separation of concerns with security-first principles:
sentinel_dv/
βββ server.py # MCP server entrypoint
βββ config.py # Security limits, feature flags, governance
βββ registry.py # Tool registration and versioning
βββ schemas/ # Typed contracts for all data
β βββ common.py # EvidenceRef, RunRef, base types
β βββ tests.py # TestCase, TestTopology, UvmTopology
β βββ failures.py # FailureEvent, FailureSignature
β βββ assertions.py # AssertionInfo, AssertionFailure
β βββ coverage.py # CoverageSummary, CoverageMetric
β βββ regressions.py # RegressionSummary, RunDiff
β βββ versioning.py # Schema version management
βββ tools/ # MCP tools (discovery + detail)
β βββ runs.py # runs.list, runs.diff
β βββ tests.py # tests.list, tests.get, tests.topology
β βββ failures.py # failures.list
β βββ assertions.py # assertions.list/get/failures
β βββ coverage.py # coverage.list/summary
β βββ regressions.py # regressions.summary
β βββ wave.py # wave.summary, wave.signals
βββ indexing/ # Artifact indexing and querying
β βββ indexer.py # Build normalized index from artifacts
β βββ store.py # DuckDB storage interface
β βββ query.py # Filter/sort/pagination
βββ adapters/ # Parse verification artifacts
β βββ uvm_log.py # UVM log parsing
β βββ cocotb.py # cocotb result parsing
β βββ assertion_reports.py # Assertion report/log parsing
β βββ coverage_reports.py # Coverage summary parsing
β βββ protocol_tags.py # Protocol taxonomy hints (AXI/APB/AHB/...)
β βββ waveform_summary.py # Precomputed *.wave.json
β βββ vcd_summary.py # VCD β bounded summary (Verilator, etc.)
βββ normalization/ # Security and determinism
β βββ signatures.py # Stable failure signature hashing
β βββ taxonomy.py # Failure categorization
β βββ redaction.py # Automatic secret/PII redaction
βββ utils/ # Common utilities
βββ hashing.py
βββ time.py
βββ bounded_text.pyDesign Principles:
Read-only by default - No simulator control, no artifact modification
Schema-first - Every response conforms to typed contracts
Deterministic - Same input β same output (no LLM-generated fields)
Evidence-based - All facts traceable to source artifacts
Bounded and safe - Automatic redaction, size limits, path sandboxing
β¨ Features
π 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
π 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)
β‘ 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
π 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
π 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
π Quick Start
PyPI: Use
sentinel-dv>=2.3.0for 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 clientβs 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-allInstallation
# 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: trueRunning 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?"
β Uses: tests.list, failures.list, tests.topology
"What assertions failed in the AXI agent?"
β Uses: assertions.failures, assertions.get
"Compare coverage between runs R123 and R124"
β Uses: runs.diff, coverage.summary
"Show me the failure signatures from the past week"
β Uses: regressions.summaryπ 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 β VCS, Questa, Cadence, Verilator, cocotb, and UVM artifact fixtures
MCP tool gallery β SVG βscreenshotsβ for all 28 tools
Verilator + VCD β Build, index, query
wave.*with time windowsVCS, Questa, and Cadence β Exported artifact fixtures and all-tool verification
cocotb + waveforms β Index
demo/treedemo/ β 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
Examples - Demo artifacts and clients
π€ 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/π Project Status
β Core schemas - Stable v1.0
β MCP tools - 28 tools (discovery, analysis, regression, waveforms, v2.0 workflow, v2.1 DV intelligence, v2.3 run/test aggregation)
β Adapters - UVM, cocotb, assertions, coverage
β Indexing - DuckDB with efficient querying
β Security - Redaction, sandboxing, bounding
β Test coverage - 70%+ with unit and integration tests
β Documentation - Full guides and API reference
β Waveform summaries -
*.wave.json+*.vcd(VcdSummaryParser); Verilator demoβ Simulator examples - VCS, Questa, and Cadence exported artifact fixtures with all-tool verification
π§ Plugin ecosystem - Coming soon
π― 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
β It does not start simulations or submit jobs
β It does not modify RTL/testbench code
β It does not require any specific simulator
β It is not an "AI that guesses"; it returns grounded, typed facts
π 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
π License
Apache License 2.0 - see LICENSE for details.
π Links
π Documentation
π¬ Discussions
π Issue Tracker
π£ Changelog
Built with β€οΈ for the verification community
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