How do I use mcp-hyperspace-memory?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-hyperspace-memory remember that I prefer concise answers with code examples" 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.

mcp-hyperspace-memory

Official

by YARlabs

Overview Schema Source Related Servers Discussions Admin

TypeScript

Hybrid

mcp-hyperspace-memory

Zero-Code cognitive memory for AI agents — powered by HyperspaceDB SaaS.
8 tools. One config block. No code required.

What is this?

mcp-hyperspace-memory is a Model Context Protocol (MCP) server that gives your AI agent a production-grade, persistent memory backed by HyperspaceDB's hyperbolic vector engine.

It is intentionally scoped to memory operations only — no DDL, no collection management, no admin tools. If you need full vector DB access, use mcp-hyperspacedb alongside it.

Related MCP server: AGI MCP Server

Quick Start

Claude Desktop / Cursor IDE / Windsurf / OpenWebUI

Add to your MCP config (claude_desktop_config.json or .cursor/mcp.json):

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "mcp-hyperspace-memory"],
      "env": {
        "HYPERSPACE_API_KEY": "<YOUR_API_KEY>",
        "MEMORY_COLLECTION": "agent_memory"
      }
    }
  }
}

That's it. Restart your agent and it will discover 8 memory tools automatically.

Get your API key at yar.ink/dashboard.

Environment Variables

Variable	Default	Required	Description
`HYPERSPACE_API_KEY`	—	✅	Database API key (`sk_...` for SaaS or your local DB password)
`HYPERSPACE_ENCRYPTION_KEY`	—	—	Client-side Zero-Knowledge encryption key (activates orthogonal/Lorentz projection + AES-256-GCM payload encryption)
`CDE_API_KEY` / `YAR_API_KEY`	—	—	Cloud API key for `v5_Embedding_801` (used when local DB has a custom password)
`MEMORY_COLLECTION`	`agent_memory`	—	Collection name to store memories in
`HYPERSPACE_HOST`	`the.yar.ink`	—	Set to `localhost:50051` to run with a self-hosted instance

🔑 Authentication Architecture: How Keys Work

Scenario 1: Managed Cloud SaaS (`the.yar.ink`)

{
  "HYPERSPACE_API_KEY": "sk_YOUR_YAR_API_KEY",
  "MEMORY_COLLECTION": "agent_memory"
}

A single sk_ key authenticates both your HyperspaceDB SaaS database storage and the v5_Embedding_801 vectorizer.

Scenario 2: Local DB (Default Security) + Cloud v5 Embeddings

{
  "HYPERSPACE_HOST": "localhost:50051",
  "HYPERSPACE_API_KEY": "sk_YOUR_YAR_API_KEY",
  "MEMORY_COLLECTION": "agent_memory"
}

Because the host is localhost and the key starts with sk_, the client connects to your local DB with default credentials (I_LOVE_HYPERSPACEDB), while forwarding sk_... to https://the.yar.ink/v1/embeddings for high-dimensional vectorization. Data stays 100% on your local disk!

Scenario 3: Local DB (Custom Password) + Cloud v5 Embeddings (Two Separate Keys)

If you configured a custom password in your local .env (HYPERSPACE_API_KEY=my_local_secret), provide two distinct keys:

{
  "HYPERSPACE_HOST": "localhost:50051",
  "HYPERSPACE_API_KEY": "my_local_secret",
  "YAR_API_KEY": "sk_YOUR_YAR_API_KEY",
  "MEMORY_COLLECTION": "agent_memory"
}

HYPERSPACE_API_KEY: Authenticates to the local gRPC server (localhost:50051).
YAR_API_KEY: Authenticates to the cloud embedding API (https://the.yar.ink/v1/embeddings).

Available Tools

Tool	Description
`memory_remember`	Store a memory, fact, or procedure with `session_id`, `memory_type` (`semantic`, `episodic`, `procedural`), `importance` (1-10), and optional `tags`
`memory_recall`	Semantic search with importance boost, recency half-life decay, and candidate oversampling, filterable by `session_id`, `memory_type`, or `min_importance`
`memory_forget`	Delete a specific memory by ID
`memory_update`	Atomically replace an existing memory (delete + store new version with refreshed embeddings)
`memory_list_sessions`	Enumerate unique active `session_id`s with multi-probe semantic discovery
`memory_explore_hierarchy`	Navigate Lorentz hyperbolic concept tree (broader vs narrower concepts)
`memory_consolidate`	Synthesize clusters of memories into a single abstract Fréchet Mean hyperbolic concept vector with optional persistence and source archiving
`memory_verify_claim`	Mathematical anti-hallucination verification using 129D MRL hybrid (Lorentz + Cosine) space with adaptive trust threshold
`memory_link`	Explicitly connect two memory/concept entities with a directed, labeled, weighted edge in the native CSR vector-graph
`memory_unlink`	Delete an explicit directed edge with zero-lag invalidation
`memory_induce_edges`	Declaratively induce knowledge graph edges across memory entries from existing metadata attributes (`path_hierarchy`, `foreign_key`, `exact_match`)
`hyperspace_query_planner`	Enterprise Query Planner & Intent Disambiguator: detects ambiguous user queries, generates multiple-choice clarifying questions, or splits compound questions into parallel sub-queries
`memory_stats`	Diagnostic status report showing vector count, collection health, and active indexing schema

🧪 Testing & Verification

Run the test suite against your cluster or local instance:

# 1. Comprehensive verification (all 9 tools + session isolation)
npm test

# 2. Brutal high-concurrency stress test (30 parallel memories, NIAH recall, Fréchet consolidation)
npm run test:stress

Architecture

Agent (Claude / Cursor)
    ↓  MCP stdio
mcp-hyperspace-memory (this package)
    ↓  gRPC / hyperspace-sdk-ts
HyperspaceDB SaaS (the.yar.ink)
    └─ MEMORY_COLLECTION  (e.g. "agent_memory")
         ├─ Lorentz head  (33D, f32, hyperbolic hierarchy)
         └─ Euclidean head (768D, 1-bit ADC, 61.4× compressed)

Key design decisions

MEMORY_COLLECTION in env: The agent never needs to pass the collection name per-call. One env var scopes all memory to the right namespace.
Deterministic IDs: Memory IDs are hash(text + session_id) — inserting the same memory twice is idempotent.
SaaS default: HYPERSPACE_HOST defaults to the.yar.ink. Self-hosted instances work by setting the env var.
No admin tools: No create_collection, delete_collection, or rebuild_index. Memory users never need these.

Comparison with `mcp-hyperspacedb`

Feature	`mcp-hyperspace-memory`	`mcp-hyperspacedb`
Target user	AI agent end-user	Developer / DevOps
Collection management	❌	✅
Cache control	❌	✅
Cognitive memory tools	✅ (8 tools)	❌
Works local + SaaS	SaaS-only	✅ both
Config complexity	1 API key	host + API key

Self-Hosting

{
  "env": {
    "HYPERSPACE_HOST": "localhost:50051",
    "HYPERSPACE_API_KEY": "I_LOVE_HYPERSPACEDB",
    "MEMORY_COLLECTION": "my_memory"
  }
}

License

This server cannot be deployed

Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

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mcp-hyperspace-memory

What is this?

Quick Start

Claude Desktop / Cursor IDE / Windsurf / OpenWebUI

Environment Variables

🔑 Authentication Architecture: How Keys Work

Scenario 1: Managed Cloud SaaS (the.yar.ink)

Scenario 2: Local DB (Default Security) + Cloud v5 Embeddings

Scenario 3: Local DB (Custom Password) + Cloud v5 Embeddings (Two Separate Keys)

Available Tools

🧪 Testing & Verification

Architecture

Key design decisions

Comparison with mcp-hyperspacedb

Self-Hosting

License

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

BuildAutomata Memory MCP

AGI MCP Server

Memsolus MCP Serverofficial

Memory Nexus MCP

Scenario 1: Managed Cloud SaaS (`the.yar.ink`)

Comparison with `mcp-hyperspacedb`