Building Tracewood: Official HydraDB Cloud SDK Integration, Architectural Constraints, and Microservice API Networks

Today, in our grand finale for Hack Hydra, we transformed Tracewood from a local prototype into a production-grade product built around HydraDB’s Official v2 Cloud API & SDK (@hydradb/sdk).

Here is everything we implemented, architectural patterns we unlocked, and how HydraDB acts as the foundational context engine for multi-agent software development.

1. Connecting Tracewood to Official HydraDB Cloud API (@hydradb/sdk v2)

Rather than assuming local database behaviors, we transitioned Tracewood to interface directly with HydraDB’s official v2 Cloud API (https://api.hydradb.com).

We built a dual-engine architecture in src/database/hydraCloud.ts that runs locally first while seamlessly syncing to Cloud HydraDB whenever HYDRA_DB_API_KEY is present in .env:

• Workspace Provisioning (client.databases.create): Auto-provisions database workspaces with structured custom metadata schemas (project, topic, intent, provider).
• Readiness Polling (client.databases.status): Polls until readyForIngestion evaluates true before streaming context.
• Dual-Store Ingestion (client.context.ingest): Ingests document ASTs, package lockfiles, and READMEs under type="knowledge", while extracting developer coding habits and architectural decisions under type="memory".

2. Architectural Constraint Invalidation Engine (Constraint Nodes & VIOLATES Edges)

AI agents refactoring code often violate historical architectural rules established weeks ago in another repository or documented in READMEs.

We built an Architectural Constraint Graph in HydraDB:

1. Automatic Extraction: AST and document parsers extract constraint rules (e.g., "Auth tokens must expire in 15 mins", "RateLimiter required on public endpoints").
2. Graph Invalidation Traversal: When an agent session refactors code, HydraDB checks historical constraint nodes (Constraint -> VALIDATES -> Symbol -> REVISED_BY -> Session).
3. Automated Prevention: If an edit conflicts with a historical rule, HydraDB establishes a VIOLATES edge, alerting the developer with a glowing 3D red warning in Tracewood and blocking invalid agent edits via MCP!

3. Cross-Repository Microservice API Dependency Graph

Package managers (package.json) only track direct code imports—failing to track implicit HTTP, gRPC, or TRPC route dependencies across microservices.

Tracewood now parses AST route handlers across all local repositories:

• Endpoint Nodes: Extracted HTTP routes (GET /api/v1/users, POST /auth/login).
• EXPOSES & CONSUMES Edges: Graph edges linking (Project)-[:EXPOSES]->(Endpoint) and (Project)-[:CONSUMES]->(Endpoint).
• Impact Simulation: Changing an API handler in your backend repo immediately reveals every frontend or sibling microservice on your machine exposed to breaking changes.

4. Dual-Store Context Fusion (type: "all") & Feedback Loop (POST /feedback)

Most AI memory tools isolate static docs from chat histories. Tracewood leverages HydraDB’s unified Dual-Store Retrieval:

• Unified Querying: Queries Knowledge and Memories in a single request (POST /query with type: "all" and mode: "thinking").
• Explicit Feedback Signal Tuning: When developers select search results or accept agent recommendations in Tracewood, we execute client.feedback.submit() with explicit ratings (positive/negative) and source: "agent" to dynamically tune retrieval rankings.

5. Full 10-Agent Telemetry Scanner & Settings Overhaul

We updated our agent detection engine to check candidate paths across macOS/Linux, auto-detecting all 10 major AI coding harnesses:

• Claude Code CLI (~/.claude)
• Google Gemini CLI / Antigravity (~/.gemini)
• Cursor IDE (~/.cursor & Application Support/Cursor)
• OpenAI Codex CLI (~/.codex)
• GitHub Copilot (~/.copilot)
• Windsurf / Codeium (~/.codeium)
• Cline / Roo Code (VS Code globalStorage)
• Aider CLI (~/.aider)
• Continue.dev (~/.continue)
• Pi / CommandCode / Factory (~/.pi)

Conclusion: Building Software as a Living 3D Garden

Tracewood demonstrates that the future of multi-agent software development isn't flat text logs or isolated chat boxes—it's an interconnected, queryable context graph.

With HydraDB at its core, Tracewood brings transparency, supply-chain safety, and long-term memory to AI pair-programming.

Code & more: https://www.dailybuild.xyz/project/229-tracewood