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Show HN: Memro – Persistent Memory for Claude Code, Cursor and Codex

Memro launched as a source-available project under the PolyForm Noncommercial License 1.0.0, giving AI coding agents such as Claude Code, Cursor and Codex persistent memory across sessions through a Go API server, Python, JavaScript/TypeScript and Go SDKs, a Model Context Protocol server and a CLI. The system stores agent identity and memory in PostgreSQL 16 with pgvector and combines vector cosine similarity with full-text keyword search via Reciprocal Rank Fusion; commercial use requires a Memro Cloud subscription or an enterprise license. The v0.1.0 release ships pinned container images (ghcr.io/memrohq/memro:0.1.0 and memro-dashboard:0.1.0) verifiable with Cosign, with the API on port 8081, dashboard on 5173 and Postgres on 55432.

read5 min views1 publishedNov 14, 2026
Show HN: Memro – Persistent Memory for Claude Code, Cursor and Codex
Image: Michielbdejong (auto-discovered)

Give your AI agents persistent memory across sessions: agent identity, memory storage and hybrid retrieval through an API, SDKs and MCP.

License (Source Available)

Memro is licensed under the PolyForm Noncommercial License 1.0.0.

Free for Non-Commercial Use: Personal study, experiments, hobby projects, research, and testing without commercial application. Commercial Use: Using Memro for commercial products or production services requires a managed subscription on Memro Cloud or an enterprise commercial license. How to Get a Commercial License: Visit memro.co/pricing or contact licensing@memro.co.

Repository Notice: github.com/memrohq/memro is the single public repository for Memro. It contains the Go server, official SDKs (Python, JavaScript/TypeScript, Go), Model Context Protocol (MCP) server, and the CLI.

npx memro-cli connect

npx memro-cli status

In your assistant, say: "Remember that our primary database is PostgreSQL 16 with pgvector."

Restart your session and ask: "What database and extensions do we use?"

Run the full Memro API server and PostgreSQL with pgvector on your own infrastructure:

git clone https://github.com/memrohq/memro && cd memro
cp .env.example .env              # add OPENAI_API_KEY for hybrid search; set METRICS_TOKEN
docker compose up -d              # API on :8081, dashboard on :5173, Postgres on 127.0.0.1:55432
curl http://localhost:8081/health
curl -fsSL https://raw.githubusercontent.com/memrohq/memro/v0.1.0/docker-compose.release.yml -o docker-compose.yml && docker compose up -d
curl http://localhost:8081/health

(Note: The prebuilt image one-liner downloads docker-compose.release.yml with pinned ghcr.io/memrohq/memro:0.1.0 and ghcr.io/memrohq/memro-dashboard:0.1.0 images, available once v0.1.0 is published.)

  • Backend API :http://localhost:8081
  • Dashboard :http://localhost:5173
  • Postgres Database : Port55432 on localhost (Option 1 clone) to avoid port 5432 collisions with existing local Postgres setups.
  • Metrics Token : SetMETRICS_TOKEN (min 32 characters) in.env to protectGET /metrics andGET /stats/cache ; the server logs a warning if unset.
  • Verify Signatures : Verify published container images keylessly using Cosign:
cosign verify ghcr.io/memrohq/memro:0.1.0 \
  --certificate-identity-regexp 'https://github.com/memrohq/memro/' \
  --certificate-oidc-issuer https://token.actions.githubusercontent.com

For complete deployment options, production topologies, and configuration tables, see docs/self-hosting.md.

┌──────────────────────────────────────┐
│         Clients & MCP Tools          │
│   Claude Code · Cursor · Codex · SDKs│
└──────────────────┬───────────────────┘
                   │  HTTP REST / Stdio MCP
┌──────────────────▼───────────────────┐
│            Memro API (Go)            │
│  Sovereign Ed25519 Identity · RRF    │
└──────────────────┬───────────────────┘
                   │  SQL & Embeddings
┌──────────────────▼───────────────────┐
│       PostgreSQL 16 + pgvector       │
│  pgvector Dense Search + tsvector FTS│
└──────────────────────────────────────┘

Memro runs a Go HTTP API backed by PostgreSQL and pgvector. Search queries combine vector cosine similarity and full-text keyword search using Reciprocal Rank Fusion (RRF,

memrohq/memro holds all components in one mono-repository:

Path Description Documentation
server/ Go API server, PostgreSQL + pgvector engine Self-Hosting Guide
cli/ One-command connector ( npx memro-cli connect ) CLI Documentation
mcp/ Model Context Protocol server (stdio & SSE HTTP) MCP Guide
sdk/python/ Official Python SDK (PyPI: memro ) Python SDK Guide
sdk/js/ Official JavaScript / TypeScript SDK (npm: @memro/sdk ) JavaScript SDK Guide
sdk/go/ Official Go SDK ( github.com/memrohq/memro/sdk/go@v0.1.0 ) Go SDK Guide
examples/ Runnable integrations (Claude Code, Cursor, Codex) Examples Index
bench/ Reproducible benchmark harness and test suites Benchmarks Index
docs/ Architecture, concepts, API reference, decisions Documentation Index
pip install memro
python
from memro import Agent

agent = Agent.create()  # local sovereign Ed25519 identity
mem = agent.remember("The billing service was rewritten in Go", type="semantic")
results = agent.recall("billing service language")
print(results[0].content)

See runnable script at examples/python/register_remember_recall.py.

npm install @memro/sdk
js
import { Agent } from '@memro/sdk';

const agent = await Agent.create(); // local sovereign Ed25519 identity
const mem = await agent.remember('The billing service was rewritten in Go', { type: 'semantic' });
const results = await agent.recall('billing service language');
console.log(results[0].content);

See runnable script at examples/typescript/index.js.

go get github.com/memrohq/memro/sdk/go@v0.1.0
package main

import (
	"context"
	"fmt"
	memro "github.com/memrohq/memro/sdk/go"
)

func main() {
	ctx := context.Background()
	agent, _ := memro.CreateAgent(nil)
	mem, _ := agent.Remember(ctx, "The billing service was rewritten in Go", nil)
	results, _ := agent.Recall(ctx, "billing service language", nil)
	fmt.Println(results[0].Content)
}

See runnable script at examples/go/main.go.

Step-by-step guides for connecting coding tools with full session-restart memory verification:

Memro includes structured primitives and cognitive graphs beyond basic vector search:

  • Typed Memories : Categorize observations assemantic (facts),episodic (events/conversations),procedural (runbooks/recipes), orprofile (agent guardrails). SeeMemory Concepts .
  • Temporal Search & Evolution : Query memories with timestamp weighting and trace how beliefs evolve over time. SeeAPI Reference .
  • Conflict Analysis & Resolution : Identify contradictory facts across sessions and mark superseded memories usingresolve_conflict() . SeeConflict Resolution .
  • Reasoning Graphs : Trace memory provenance, causal chains, and dependencies between stored observations. SeeOpinionated Guide .

Memro publishes empirical evaluations and methodology:

  • LongMemEval Benchmark : Evaluated across 500 questions testing multi-session recall and knowledge updates. SeeLongMemEval Report .
  • Empirical Failure & Boundary Evaluations : Runnable test suite for identity boundaries, contradictory facts, stale facts, and distractor rejection. SeeMeasurable Evaluations .
  • Clean-Machine Verification : Full transcript verifying every quickstart command in a container without local caches. SeeVerification Transcript .
docker compose up -d db

cd server
DATABASE_URL=postgres://memro:memro@localhost:55432/memro go run ./cmd/memro-api

MEMRO_TEST_DATABASE_URL=postgres://memro:memro@localhost:55432/memro go test -race ./...

Please review CONTRIBUTING.md and SECURITY.md before submitting pull requests.

Repository: github.com/memrohq/memro · Documentation: https://memro.co License: Source available under PolyForm Noncommercial 1.0.0. Free for non-commercial use; commercial use requires Memro Cloud or a commercial license.

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