cortex-engine
Integrates Hugging Face as a pluggable LLM provider for AI agents.
Provides local LLM and embedding support as pluggable providers for AI agents.
Integrates OpenAI as a pluggable LLM and embedding provider for AI agents.
Serves as a local storage backend for persistent memory (default).
Click on "Deploy 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., "@cortex-engineremember that I like dark mode in my editor"
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.
@fozikio/cortex-engine
Persistent memory for AI agents. Open source, LLM-agnostic, works with any MCP client.
Star History
Related MCP server: Memory Search MCP Server
What It Does
Most AI agents forget everything when the session ends. cortex-engine fixes that — it gives agents a persistent memory layer that survives across sessions, models, and runtimes.
Semantic memory — store and retrieve observations, beliefs, questions, and hypotheses as interconnected nodes
Belief tracking — agents hold positions that update when new evidence contradicts them
Two-phase dream consolidation — NREM compression (cluster, refine, create) + REM integration (connect, score, abstract) — modeled on biological sleep stages
Goal-directed cognition —
goal_setcreates desired future states that generate forward prediction error, biasing consolidation and exploration toward what mattersNeuroscience-grounded retrieval — GNN neighborhood aggregation, query-conditioned spreading activation, multi-anchor Thousand Brains voting, epistemic foraging
Information geometry — locally-adaptive clustering thresholds that respect embedding space curvature, schema congruence scoring
Graph health metrics — Fiedler value (algebraic connectivity) measures knowledge integration; PE saturation detection prevents identity model ossification
Spaced repetition (FSRS) — interval-aware scheduling with consolidation-state-dependent decay profiles
Embeddings — pluggable providers (built-in, OpenAI, Vertex AI, Ollama) — no external service required by default
LLM-agnostic — pluggable LLM providers: Ollama (free/local), Gemini, Kimi (Moonshot AI), DeepSeek, Hugging Face, OpenRouter, OpenAI, or any OpenAI-compatible API
Three storage backends — local SQLite (default), cloud Firestore, and JSON file (backup/migration). All share one
CortexStoreinterface — see docs/storage-backends.mdAtomic transactions —
withTransaction(fn)primitive composes multi-step writes. SQLite usesBEGIN IMMEDIATEwith a per-store mutex; Firestore usesrunTransactionwith a write-routing proxy. See docs/concurrency.mdMigration tooling —
fozikio migrate --from <url> --to <url>clones between any pair of backends. ID-preserving, checkpointed, resumable, fails-loud on schema mismatchTyped tool catalogue — every cognitive tool carries
category+whenToUse+doNotUsemetadata so LLMs disambiguate cleanly. Browse withfozikio toolsorGET /tools. Auto-generated reference at docs/tools-reference.mdLong-context dream consolidation — set
strategy: long-contextto run edge discovery and abstraction in a single large LLM pass instead of N² pairwise calls; surfaces transitive patterns and cross-domain connections that the sequential approach missesAgent dispatch —
agent_invokelets your agent spawn cheap, cortex-aware sub-tasks using any configured LLM. Knowledge compounds across sessions.MCP server — 60 cognitive tools (
query,observe,believe,wander,dream,goal_set,agent_invoke,thread_create,journal_write,evolve, etc.) over the Model Context Protocol
The result: personality and expertise emerge from accumulated experience, not system prompts. An agent with 200 observations about distributed systems doesn't need to be told "you care about distributed systems." It just knows.
Works with Claude Code, Cursor, Windsurf, or any MCP-compatible client. Runs locally (SQLite) or in the cloud (Firestore + Cloud Run).
Security
The engine includes defense-in-depth protections for deployed environments:
Timing-safe auth — REST server authentication uses
crypto.timingSafeEqualto prevent timing side-channel attacksPlugin sandboxing — the plugin loader validates import paths against trusted directories, blocking loads from untrusted locations
REST tool blocklist — destructive tools (
forget,dream,evolve,resolve,thread_resolve) are blocked from the generic REST endpoint; they remain available via MCP for direct agent accessSQLite injection prevention — namespace names are validated (alphanumeric only), LIMIT clauses are parameterized
Secret leak prevention — config loader warns when API keys appear in config files instead of environment variables
Known advisories
npm install @fozikio/cortex-engine reports 0 vulnerabilities.
This section previously documented three moderate advisories from
@hono/node-server, pulled in transitively by the MCP SDK and unreachable here
(the MCP server runs over stdio, which never mounts serve-static). That chain
has since been fixed upstream: @modelcontextprotocol/sdk@1.30.0 accepts
@hono/node-server ^2.0.5, and this package now requires SDK ^1.30.0 so the
patched range resolves for every install rather than by chance.
Architecture
Module | Role |
| Foundational types, config, and shared utilities |
| Cognitive processing: memory consolidation, FSRS, graph traversal |
| Persistence layer — SQLite (local), Firestore (cloud), JSON (backup/migration). All implement the shared |
| All 60 cognitive tool implementations (one file per tool) |
| MCP server, tool registry, and plugin loader |
| Higher-order cognitive operations (dream, wander, validate) |
| Scheduled and event-driven triggers |
| Adapters for external services and APIs |
| Embedding and LLM provider implementations |
| Entry points: |
Quick Start
npm install @fozikio/cortex-engine
npx fozikio init my-agent
cd my-agent
npx fozikio serve # starts MCP serverYour agent now has 60 cognitive tools. The generated .mcp.json is version-pinned and platform-aware (Windows cmd /c wrapper handled automatically).
See the Quick Start guide for the full 5-minute setup.
Multi-Agent
npx fozikio agent add researcher --description "Research agent"
npx fozikio agent add trader --description "Trading signals"
npx fozikio agent generate-mcp # writes .mcp.json with scoped serversEach agent gets isolated memory via namespaces. See the Architecture section for details.
Agent-First Setup
The fastest path: open an AI agent in an empty directory and say "set up a cortex workspace." The agent runs npx fozikio init, reads the generated files, and is immediately productive. See the Agent-First Setup guide for the full walkthrough.
Dashboard
No dashboard currently ships with the package. Releases 1.0.0 through 1.2.1 bundled one; it stopped being included at 1.2.2 when publishing moved to CI, and it is not coming back in its old form — see #59 for what a replacement needs.
The REST server still serves one. On startup it looks for public/index.html next to dist/, and if it finds it, serves that directory as a single-page app — assets first, index.html as the fallback route, with /api/* and /health reserved. Static assets bypass auth; the API calls the page makes do not. So you can drop any built front-end into public/ and it will be served from the same origin as the API:
npx fozikio serve --rest --port 3000
# with public/index.html present, open http://localhost:3000If auth is enabled (CORTEX_API_TOKEN), a page served this way loads without auth but its API calls need a token. The old dashboard read one from localStorage:
localStorage.setItem("cortex-settings", JSON.stringify({ token: "your-token" }));The previous UI's source is Fozikio/dashboard — a Vite/React build that still compiles, but predates the REST and CLI changes in 1.3.0 and 1.4.0 and has not been re-integrated.
CLI
Run fozikio with no arguments for an interactive session — a prompt with tab
completion, history, and a filterable command palette on an empty enter:
fozikio 1.3.0
● ollama ● nli
enter a command · empty enter to browse · ? help · exit quit
fozikio ›Or use it directly:
npx fozikio doctor # diagnose the install, with fixes
npx fozikio dashboard # live service and memory view
npx fozikio up # start every service, wait until ready
npx fozikio status # service status (exit 1 if unhealthy)
npx fozikio down # stop every service
npx fozikio serve # start MCP serverServices. The default setup (--embed ollama --llm ollama, plus NLI adjudication)
depends on two background daemons: ollama on :11434 and the NLI cross-encoder on
:11435. When either stops answering, every semantic tool — query, observe,
wonder, dream — fails while ops, threads and journal keep working, so the failure
is easy to miss. fozikio supervises both:
npx fozikio service start nli # start detached, wait for the probe
npx fozikio service status # per-service state
npx fozikio service logs ollama --lines 50 # tail ~/.fozikio/logs/
npx fozikio service restart ollama
npx fozikio up --watch # restart on failure, with backoffA service counts as up when its HTTP endpoint answers, not when its process exists —
a process that is alive but no longer responding reports as degraded, which is the
failure this is built to catch.
Memory.
npx fozikio memory health # memory health report
npx fozikio memory vitals # behavioral vitals and prediction error
npx fozikio memory wander --from "auth" # seeded walk through the graph
npx fozikio memory maintain fix # scan and repair data issues
npx fozikio memory report # weekly quality report
npx fozikio tools --category memory # browse the cognitive tool catalogue
npx fozikio migrate --from sqlite:./cortex.db --to json:./backup.json --verifyThe pre-memory spellings (fozikio health, fozikio vitals, …) still work and are
not deprecated — existing scripts need no changes.
Every command takes --json for machine-readable output and honours NO_COLOR;
styling and progress indicators switch off automatically when output is piped.
--yes skips confirmations for unattended use. Read-only commands honour
--namespace <ns> and --agent <name>; in a workspace with .fozikio/agent.yaml,
the agent's default_namespace is picked up automatically — no flag needed.
Development
npm run dev # tsc --watch
npm test # vitest run
npm run test:watchEnvironment Variables
Variable | Required | Description |
| Optional | Used by the |
| Optional | Required when |
| Optional | Required when |
| Optional |
|
| Optional |
|
| Optional |
|
| Optional | Path to the SQLite file, e.g. a mounted volume ( |
Additional variables are required depending on which providers you enable (Firestore, Vertex AI, etc.). See docs/ for provider-specific configuration, and docs/deploy-railway.md for a hosted deployment with no Ollama — or use the one-click template:
Rules, Skills & Agents
fozikio init automatically installs safety rules, skills, and agent definitions from the fozikio.json manifest into the target workspace.
Safety Rules (Reflex)
cortex-engine ships with Reflex rules — portable YAML-based guardrails that work across any agent runtime, not just Claude Code.
Rule | Event | What It Does |
|
| Nudges the agent to call |
|
| Warns if writing to memory directories without calling |
|
| Suggests capturing new threads of thought with |
Rules live in reflex-rules/ as standard Reflex YAML. They're portable — use them with Claude Code, Cursor, Codex, or any runtime with a Reflex adapter. See @fozikio/reflex for the full rule format and tier enforcement.
Claude Code users also get platform-specific hooks (in hooks/) for telemetry, session lifecycle, and project board gating. These are runtime adapters, not rules — they handle side effects that the declarative rule format doesn't cover.
To customize: Edit the YAML rule files directly, or set allow_disable: true and disable them via Reflex config.
Skills
Skills are invocable workflows that agents can use via /skill-name.
Skill | When to Use | What It Provides |
| Query, record, and review work | Full memory workflow — query/observe patterns, belief tracking, memory-grounded code review, session patterns |
Agents
Agent | Description |
| Deep research agent that queries cortex before external sources, observes novel findings back into memory |
How Auto-Install Works
fozikio initreadsfozikio.jsonfrom the package rootCopies hooks, skills, and Reflex rules into the target workspace
Missing source files are skipped with a warning — init never fails due to missing assets
Built-in Capabilities (v1.0.0+)
As of v1.0.0, all 60 cognitive tools are built into cortex-engine core — no separate plugin installs needed. Previously these were separate @fozikio/tools-* packages; they've been absorbed into the engine.
Capability | Tools |
Memory |
|
Beliefs & Reasoning |
|
Threads |
|
Journaling |
|
Identity |
|
Social |
|
Graph |
|
Maintenance |
|
Vitals |
|
Reasoning |
|
Content |
|
Ops |
|
Goals |
|
Agents |
|
Stats |
|
The plugin system is still available for custom extensions — see Plugin Docs.
Documentation
In-repo docs:
Quick Start — 5-minute setup
Storage backends — SQLite vs Firestore vs JSON, migration paths
Concurrency model —
withTransactioncontract, single-process invariant, SQLite vs Firestore semanticsTools reference — all 60 tools by category with when-to-use guidance (auto-generated)
Multi-agent design — namespace isolation, bridges, federation
Design specs — design documents from the v1.2.0 audit-driven refactor
Agent-first setup — Workspace initialization walkthrough
Discussions — Ask questions, share what you've built
Contributing — How to contribute
Project Board — Roadmap and active work
Security — Report vulnerabilities
Community
r/Fozikio — Project subreddit
GitHub Discussions — Questions, feedback, show what you've built
"I built 44 MCP tools for my cognitive system" — r/mcp deep dive (84 upvotes, 27 comments)
"Gave my agent a subconscious" — r/clawdbot walkthrough (22 upvotes, 34 comments)
Related Projects
@fozikio/reflex — Portable safety guardrails for agents. Rules as data, not code.
sigil — Agent control surface. Signals and gestures, not conversations.
fozikio.com — Documentation and guides
License
MIT — see LICENSE
This server cannot be deployed
Maintenance
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