Show HN: Agentic Data Kernal

Jason Doyle released Agentic Data Kernel 0.2.0-alpha.1, an open-source data infrastructure system for long-running software agents that manages knowledge, workflow state, and external effects with bitemporal assertions, hybrid retrieval, and PostgreSQL row-level security. The project, forked from a private project and maintained independently, offers development and PostgreSQL runtime profiles and is available via npm as 'agentic-data-kernel'.

Author note, 2 September 2026, Jason DoyleThis project began as a feature forked from a private project and is now maintained independently as open source. The documentation is heavily AI assisted and may contain errors. Verify important behavior against the implementation, tests, and current release before using it in production. Open source data infrastructure for long-running software agents. Agentic Data Kernel keeps knowledge, workflow state, and external effects in a single governed system. It is designed for applications that need to answer: - What is currently known? - When was it valid? - Where did it come from? - What conflicts with it? - Which workflow or external action depended on it? - Bitemporal assertions with evidence, epistemic kind, perspective, and typed uncertainty - Explicit known , unknown , and conflicted resolution results - Hybrid lexical, vector, relational, graph, and temporal retrieval - Durable workflow state, timers, idempotency, and execution receipts - Transactional inventory reservations and payment effect intents - Scoped API keys, purpose binding, and PostgreSQL row-level security - Encrypted immutable artifact storage with key rotation - Authorized effect delivery with budgets, retries, and status reconciliation - HTTP, MCP, TypeScript, CLI, and read-only local SQL interfaces | Use case | What the kernel provides | |---|---| | Catalog and master-data reconciliation | Source-backed claims, conflicting values, temporal correction, and reviewable resolution | | Persistent agent memory | Distinct observations, facts, inferences, decisions, and experiences with provenance | | Retail order workflows | Inventory holds, expiry timers, payment effects, idempotent retries, and durable order state | | Customer support operations | Tenant-scoped context retrieval, current-state checks, and evidence-linked decisions | | Incident response | Temporal observations, hypotheses, workflow history, and controlled remediation effects | | Controlled payment automation | Purpose-scoped credentials, effect budgets, authorization fences, and audit receipts | See docs/USE CASES.md /Jason-Doyle/agentic-data-kernal/blob/main/docs/USE CASES.md for detailed flows and current support. The current release is 0.2.0-alpha.1 . Two runtime profiles are maintained: Development profile: embedded SQLite, loopback HTTP, local MCP, and read-only SQL for inspection. PostgreSQL profile: PostgreSQL 18, pgvector, forced tenant isolation, authenticated APIs, encrypted artifacts, provider embeddings, effect workers, TLS, migrations, metrics, backup, restore, and load tooling. The PostgreSQL profile targets bounded single-primary deployments. See docs/PRODUCTION.md /Jason-Doyle/agentic-data-kernal/blob/main/docs/PRODUCTION.md before exposing it outside a trusted environment. Install the TypeScript library: npm install agentic-data-kernel@next Run the embedded example without cloning the repository: npx --yes agentic-data-kernel@next example --db .data\example.db Published prereleases use the npm next tag. Production applications should pin an exact package version. js import { AgenticKernel, SqliteStore } from "agentic-data-kernel"; const store = new SqliteStore ".data/app.db" ; const kernel = new AgenticKernel store ; The npm package provides: agentic-data-kernel and agentic-data for the embedded CLI; agentic-data-prod for production administration and runtime commands; agentic-data-kernel/production for PostgreSQL integrations. Requirements: - Node.js 22.19 or newer - npm 10 or newer npm install npm run build npm test npm run example The sample workflow: - stores conflicting supplier claims about a product; - preserves both claims and returns an explicit conflict; - searches across a customer, product, and incident graph; - reserves inventory transactionally; - creates a durable payment effect; - records the provider outcome; - confirms the order without duplicating inventory changes on replay. The sample database is written to .data\example.db . Node's built-in node:sqlite API is experimental in Node 22. This affects only the development profile. Build: npm run build Initialize a database: node --no-warnings dist\cli.js init --db .data\agentic.db Execute an operation: node --no-warnings dist\cli.js execute --db .data\agentic.db --file examples\put-product.json Inspect state with read-only SQL: node --no-warnings dist\cli.js sql --db .data\agentic.db --query "SELECT assertion id, predicate, status FROM assertions" The SQL interface accepts SELECT , EXPLAIN , and schema-inspection PRAGMAs. npm run serve Default address: http://127.0.0.1:4318 | Route | Purpose | |---|---| GET /health | Liveness | GET /v1/catalog | Supported operations and guarantees | POST /v1/execute | Execute one Agent Intent operation | The development server is loopback-only and has no network SQL route. Start the development MCP server from a published package: npx --yes agentic-data-kernel@next mcp --db .data\agentic.db Or start it from a source checkout: npm run mcp It publishes agentic-data://catalog and these tools: execute intent search knowledge resolve claims reserve inventory get machine Use npm run prod:mcp for an authenticated PostgreSQL-backed MCP process. | Example | Command | |---|---| | TypeScript library | npm run example:library | | MCP client | npm run example:mcp | | Authenticated production HTTP | npm run example:production-http | | Production retail workflow | npm run example:production-retail | | Embedding provider | npm run example:embedding | | Embedding protocol helper | npm run example:mock-embeddings | | Effect receiver contract | npm run example:mock-effects | Setup, environment variables, and receiver contracts are documented in docs/INTEGRATIONS.md /Jason-Doyle/agentic-data-kernal/blob/main/docs/INTEGRATIONS.md . Requirements: - Docker with Compose - An OpenAI-compatible 1536-dimensional embedding endpoint - Generated database, authentication, and artifact-encryption secrets Use the versioned production image: Copy-Item .env.example .env .\scripts\generate-secrets.ps1 $env:AGENTIC DATA IMAGE = "ghcr.io/jason-doyle/agentic-data-kernel:0.2.0-alpha.1" docker compose --profile server pull docker compose --profile server up --no-build Or build the image from the checked-out source: Copy-Item .env.example .env .\scripts\generate-secrets.ps1 docker compose --profile server up --build The included deployment: - creates a non-superuser runtime database role; - applies checksum-verified migrations separately; - initializes artifact-directory ownership; - runs the API and effect worker independently; - publishes only the Caddy TLS endpoint; - keeps PostgreSQL bound to loopback by default. Full setup and operating procedures are in docs/PRODUCTION.md /Jason-Doyle/agentic-data-kernal/blob/main/docs/PRODUCTION.md . Version 0.1 executes one typed operation per envelope: { "protocolVersion": "0.1", "requestId": "claim-1", "idempotencyKey": "claim-1", "principal": { "tenantId": "example-retail", "principalId": "catalog-agent", "purpose": "catalog-ingestion" }, "operation": { "op": "assert", "assertion": { "subjectEntityId": "product:sku-17", "predicate": "packaged weight", "object": { "type": "number", "value": 4.8, "unit": "kg" }, "kind": "reported fact", "strength": { "type": "rank", "value": "normal" } } } } The production server derives authority from the authenticated API key and rejects envelopes whose tenant, principal, or purpose does not match. HTTP / MCP / TypeScript / CLI | Agent Intent validation | identity, scope, purpose | knowledge + workflow kernel | assertions and evidence | conflict resolution | hybrid retrieval | timers and state machines | effects and receipts | SQLite development adapter or PostgreSQL + pgvector + RLS Use cases /Jason-Doyle/agentic-data-kernal/blob/main/docs/USE CASES.md Benefits and tradeoffs /Jason-Doyle/agentic-data-kernal/blob/main/docs/TRADEOFFS.md Integration guide /Jason-Doyle/agentic-data-kernal/blob/main/docs/INTEGRATIONS.md API reference /Jason-Doyle/agentic-data-kernal/blob/main/docs/API.md Production profile /Jason-Doyle/agentic-data-kernal/blob/main/docs/PRODUCTION.md Release process /Jason-Doyle/agentic-data-kernal/blob/main/docs/RELEASING.md Threat model /Jason-Doyle/agentic-data-kernal/blob/main/docs/THREAT MODEL.md Security policy /Jason-Doyle/agentic-data-kernal/blob/main/SECURITY.md Contributing /Jason-Doyle/agentic-data-kernal/blob/main/CONTRIBUTING.md Support /Jason-Doyle/agentic-data-kernal/blob/main/SUPPORT.md Code of conduct /Jason-Doyle/agentic-data-kernal/blob/main/CODE OF CONDUCT.md Changelog /Jason-Doyle/agentic-data-kernal/blob/main/CHANGELOG.md - The included deployment uses one PostgreSQL primary. - The default rate limiter is process-local. - The vector schema currently requires 1536-dimensional embeddings. - Effect receivers must honor idempotency keys. - Projection epochs, multi-operation plans, and context-package optimization are not yet implemented. Apache-2.0. See LICENSE /Jason-Doyle/agentic-data-kernal/blob/main/LICENSE .