Part of the StudioMeyer MCP Stack — Built in Mallorca 🌴 · ⭐ if you use it

StudioMeyer Memory

Persistent, intelligent memory for AI agents. 53 MCP tools. Knowledge Graph included in every plan.

What is this?

StudioMeyer Memory gives AI agents persistent memory across sessions. Instead of starting fresh every conversation, your agents learn, remember, and improve over time.

53 MCP tools for learning, search, knowledge graph, session tracking, multi-agent support, contradiction detection, and self-improvement.

Connect in 10 Seconds

Claude Desktop / Cowork

Settings → Connectors → Add URL:

https://memory.studiomeyer.io/mcp

Claude Code

claude mcp add --transport http memory https://memory.studiomeyer.io/mcp

Cursor / VS Code / Windsurf / Zed

npx mcp-remote https://memory.studiomeyer.io/mcp

MCPize

npx mcp-remote https://studiomeyer-memory.mcpize.run

REST API

For custom agents, scripts, and integrations:

# 1. Sign up
curl -X POST https://memory.studiomeyer.io/api/signup \
  -H "Content-Type: application/json" \
  -d '{"email": "you@example.com"}'

# 2. Store a memory
curl -X POST https://memory.studiomeyer.io/api/learn \
  -H "Authorization: Bearer nex_your_key" \
  -H "Content-Type: application/json" \
  -d '{"category": "insight", "content": "Users prefer dark mode"}'

# 3. Search
curl -X POST https://memory.studiomeyer.io/api/search \
  -H "Authorization: Bearer nex_your_key" \
  -H "Content-Type: application/json" \
  -d '{"query": "user preferences"}'

API Endpoints

Method	Endpoint	Description
POST	/api/signup	Create account, get API key
GET	/api/account	Account info, plan, limits
POST	/api/learn	Store a learning
POST	/api/search	Search all knowledge
POST	/api/decide	Log a decision
POST	/api/entity	Create/update entity
POST	/api/import	Import from ChatGPT/Claude/Gemini/Copilot/Perplexity
POST	/api/backfill	Generate embeddings
GET	/api/export	Export all data (Markdown)
POST	/api/checkout	Upgrade plan (Stripe)

Full API documentation: openapi.yaml

SDKs

• TypeScript: npm install @studiomeyer/memory-sdk (GitHub)
• Python: pip install nex-memory (GitHub)
• OpenAPI Spec: openapi.yaml — generate clients for any language

Features

Core Memory

• 5-phase parallel search — semantic vectors, trigram matching, full-text, graph traversal, pattern matching
• Duplicate detection — 5-factor admission control prevents noise
• 10 learning categories — pattern, mistake, insight, research, architecture, and more
• Decision logging — track choices with reasoning for traceability

Knowledge Graph (All Plans)

• Entities — people, tools, projects, concepts
• Observations — facts attached to entities with temporal validity
• Relations — typed, directional connections between entities
• Graph traversal — 2-hop BFS search through connections
• Temporal queries — "What was true on March 15th?"

Intelligence

• Contradiction Detection — automatically flags conflicting facts
• FadeMem Adaptive Decay — important memories fade 6x slower
• Confidence Scoring — 0-1 scores with temporal decay
• Bi-temporal Model — event time + ingestion time
• Auto-Consolidation — merges duplicates, backfills embeddings

Multi-Agent

• Agent namespaces — scope memories to specific agents
• Cross-agent search — search across all agents by default
• Shared Knowledge Graph — one graph, multiple agents

Import

• 5 platforms — ChatGPT, Claude, Gemini, GitHub Copilot, Perplexity
• LLM extraction — entities, learnings, decisions, relations
• Preview mode — analyze before importing

Benchmark — Work in Progress

A 10-question stratified pre-flight run on LongMemEval v3 (April 2026, GPT-4o scoring) returned 90% — useful as a smoke test but too small to be the official number.

The first full 50-question run came in lower. We are currently in the 60 to 80 percent range, with a clear upward trajectory. The next clean 50-question multi-category run is scheduled for the coming days, including an assistant-ingest fix and Sonnet 4.5 as the answer generator. We will publish the final score, methodology and full run logs as soon as that run completes — that will be the official number.

Publicly published scores from other vendors (for reference):

System	Score	Source
Mastra Observational Memory	94.87%	gpt-5-mini, public leaderboard
Hindsight	91.4%	published
Zep	63.8%	arXiv 2501.13956

Pricing

Plan	Price	Calls/Day	Learnings	Knowledge Graph
Free	$0 forever	200	1,000	✅
Pro	$29/mo	5,000	25,000	✅
Team	$49/mo	Unlimited	Unlimited	✅

All 53 tools available in every plan. Knowledge Graph included from Free.

Compare: Mem0 charges $249/mo for Graph Memory. We include it for free.

Security

• Magic Link Authentication — email verification on every sign-in. No passwords stored. You receive a single-use link that expires in 10 minutes. Nobody can access your data without proving email ownership.
• OAuth 2.1 with PKCE S256 — latest authentication standard
• Supabase Pro (EU Frankfurt, Germany) — SOC 2 Type II, GDPR-ready
• Row Level Security — tenant isolation at database level
• Secret Scanner — prevents accidental storage of API keys/passwords
• Data Export — GET /api/export anytime
• Encryption — at rest (AES-256) and in transit (TLS 1.3)

Examples

See the examples/ folder:

• Python basic usage
• LangChain integration
• CrewAI multi-agent
• TypeScript basic
• ChatGPT import
• Official SDK usage

Resources

• Documentation: Built-in — call nex_guide("quickstart") via MCP
• Postman Collection: Download
• OpenAPI Spec: openapi.yaml
• MCP Registry: io.studiomeyer/memory

Built By

StudioMeyer — AI agency based in Spain. Building intelligent systems since 2024.

License

MIT — see LICENSE. The memory server is a hosted service — this repository contains documentation and examples.

Links

• 🌐 memory.studiomeyer.io
• 🏪 MCPize Marketplace
• 🏢 studiomeyer.io