Cortex
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., "@Cortexsave the hydration bug fix to project memory: we moved the fetch out of useEffect"
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.
The problem
Your coding agent solves a nasty bug on Tuesday. On Wednesday it opens a fresh context window and has no idea that bug ever existed. You paste the same explanation again.
Cortex gives the agent a memory it writes to and reads from by itself, through MCP:
structured memories (bug_fix, decision, discovery, pattern, preference, ...),
scoped per project, ranked by relevance, decayed over time, and re-surfaced when the same
symptom shows up again.
Everything lives in a single SQLite file on your machine (~/.memoria/memoria.db).
No account, no API key, no telemetry.
Related MCP server: exocortex
What's in the box
20 MCP tools — save / search / context / recall / hint / feedback / sessions / reflections / forget (full list).
Hybrid retrieval — SQLite FTS5 keyword search fused with vector KNN via Reciprocal Rank Fusion. Embeddings are optional and run locally (
@xenova/transformers, 384-dim MiniLM, ~22 MB, CPU).Outcome-aware trust — the agent reports back whether a surfaced memory helped, was stale or misled it (
memoria_feedback); trust scores re-rank future results.Proactive hints —
memoria_hinttakes the upcoming tool call / prompt / file path and returns up to 3 short hints to inject before acting.Reflections — a CPU-only clustering pass groups related memories; your agent's LLM synthesizes the meta-lesson (Cortex never calls an LLM itself).
Decay & forget — relevance decays,
memoria_forgetpreviews (dry-run by default) and soft-deletes the floor.Privacy by default — API keys, PATs, JWTs, SSH keys and
<private>...</private>blocks are stripped before anything is written to disk.Ops-ready — structured JSON logs, Prometheus metrics at
/api/metrics, quotas, optional bearer auth, multi-tenant workspaces.
Quickstart (2 minutes)
Requirements: Node >= 20 (verified on 22 and 26), git. better-sqlite3 compiles or
downloads a prebuilt binary on install — no other system dependency.
git clone https://github.com/gonzalonicolasr/cortexmem.git
cd cortexmem
npm install
npm test # optional: 216 tests, ~1sOr install it without cloning — you get a cortexmem command on your PATH:
npm install -g github:gonzalonicolasr/cortexmem
cortexmem --versionSmoke test it as a plain CLI:
node bin/memoria.mjs save "Fix hydration bug" \
--type bug_fix --what "moved the fetch out of useEffect" \
--project demo --learned "SSR/CSR mismatch, not a race condition"
node bin/memoria.mjs search hydration --project demo
node bin/memoria.mjs statsThat's it — the database was created at ~/.memoria/memoria.db on first write.
Plug it into your agent
Cortex speaks MCP over stdio. If you installed globally, the command is cortexmem mcp;
from a clone, use node with the absolute path to bin/memoria.mjs.
claude mcp add cortex -- node /absolute/path/to/cortexmem/bin/memoria.mjs mcp
claude mcp list | grep cortex # → ✓ Connected[mcp_servers.cortex]
command = "node"
args = ["/absolute/path/to/cortexmem/bin/memoria.mjs", "mcp"]{
"mcpServers": {
"cortex": {
"type": "stdio",
"command": "node",
"args": ["/absolute/path/to/cortexmem/bin/memoria.mjs", "mcp"]
}
}
}Install an MCP extension for pi and point it at the same command/args pair as the JSON
example above. For the HTTP transport, see docs/self-hosting.md.
Restart the client after editing its config — Codex and Claude Code do not re-read it hot.
Teach the agent to actually use it
Tools alone are not enough: the agent has to know when to write. Copy
CLAUDE.md (the memory protocol) into your agent's instruction file
(CLAUDE.md, AGENTS.md, .cursorrules, pi's AGENTS.md, ...). It's ~40 lines and tells
the agent to save automatically after bug fixes, decisions, discoveries and config changes,
and to call memoria_context at session start.
CLI
memoria mcp Start the MCP server (stdio)
memoria serve [port] Start the HTTP API (default 7437, loopback-only)
memoria save <title> [flags] Save a memory
memoria search <query> Full-text search
memoria context [project] Print the project context block
memoria recent [flags] Recent memories
memoria stats Counts by type / project
memoria projects List projects
memoria decay Apply relevance decayFlags: --project --type --limit --what --why --where --learned --topic.
Server mode
Want one memory shared by every machine / agent in your homelab? Run the HTTP API and front it with a reverse proxy:
MEMORIA_HOST=127.0.0.1 MEMORIA_AUTH_TOKEN=$(openssl rand -hex 24) \
node bin/memoria.mjs serve 7437
curl -s localhost:7437/api/healthEndpoint reference: docs/http-api.md.
systemd unit, bearer auth, embeddings backfill, reflection cron and backups:
docs/self-hosting.md.
⚠️ The HTTP server trusts the
X-Workspace-Idheader (multi-tenant design: an upstream proxy validates the user and injects it). Never bind it to a public interface withoutMEMORIA_AUTH_TOKEN+ a proxy in front.
Semantic search (optional)
npm install @xenova/transformers # already an optionalDependency
export MEMORIA_SEMANTIC_SEARCH=1
node bin/backfill-embeddings.mjs # embed existing memoriesThe model downloads once (~22 MB) and runs on CPU. With the flag on, memoria_search and
memoria_recall become hybrid (FTS5 + KNN fused with RRF); with it off, everything still
works as pure keyword search. Non-English memories: set
MEMORIA_EMBEDDING_MODEL=Xenova/paraphrase-multilingual-MiniLM-L12-v2 before the
backfill (same 384 dims) — see semantic search.
Environment variables
Variable | Default | What it does |
|
| Directory holding |
| — | Explicit DB file (wins over |
| auto-detected from cwd | Override project detection |
|
| Workspace used by CLI/stdio |
|
| HTTP bind |
| — | If set, HTTP requires |
| off |
|
|
| Any 384-dim feature-extraction model |
| transformers default | Where model files are cached |
| off |
|
| — | CSV of workspace ids exempt from quotas — set it to |
Quotas
Defaults are sized for the multi-tenant hosted deployment: 1 000 active memories, 10 MB of logical text, 50 projects, 5 active sessions, 32 KB per memory. For a personal local install, lift them:
export MEMORIA_UNLIMITED_WORKSPACES=1 # workspace 1 = the CLI/stdio defaultMCP tools
Tool | Use it for |
| Persist a structured memory ( |
| Hybrid/keyword search |
| Project context block; can open a session in the same call |
| "Have I seen this error before?" — symptom → past fixes |
| Proactive pre-tool-call hints (≤3, short) |
| Report |
| Meta-lesson synthesis loop |
| Hygiene: decay preview + soft-delete floor |
| Session lifecycle with structured summary |
| Memory maintenance & browsing |
| Introspection & project metadata |
| Store what the user asked, verbatim |
Tool names keep the memoria_ prefix (the project's original name) for backwards
compatibility with existing installs.
Data, privacy, backups
One SQLite file (WAL mode). Back it up with
sqlite3 ~/.memoria/memoria.db ".backup out.db".Secrets are stripped before the row is written: AWS keys, GitHub/GitLab PATs, OpenAI/Anthropic/Slack/Google/Stripe/Cloudflare keys, JWTs, SSH private keys, and anything you wrap in
<private>...</private>. It's a safety net, not a licence to paste secrets.Nothing leaves your machine unless you run the HTTP server and expose it.
Development
npm test # vitest, 216 tests
npm run test:watchMultilingual embedding tests are gated behind MEMORIA_TEST_MULTILINGUAL=1 so the normal
suite never downloads a model. Changelog: CHANGELOG.md.
Hosted (optional)
If you'd rather not run anything, the same engine is hosted at
cortexmem.com: sign up, copy the cc_... API key from the panel,
and point your client at the HTTP endpoint instead of the local command:
claude mcp add cortex https://cortexmem.com/api/cortex/mcp \
--transport http --header "Authorization: Bearer cc_YOUR_KEY"# ~/.codex/config.toml
[mcp_servers.cortex]
url = "https://cortexmem.com/api/cortex/mcp"
[mcp_servers.cortex.http_headers]
Authorization = "Bearer cc_YOUR_KEY"Self-hosting stays fully featured — the hosted tier adds the web panel and the brain graph, not the memory itself.
License
MIT © Gonzalo Rocca — see LICENSE.
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