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mcp-hyperspacedb

v3.0.3

Published

MCP server for HyperspaceDB - high performance multi-geometry vector database

Readme

HyperspaceDB MCP Server

MCP TypeScript HyperspaceDB

The HyperspaceDB MCP Server acts as a high-performance cognitive bridge, enabling Large Language Models (LLMs) to interact with HyperspaceDB — a multi-geometry vector database designed for advanced AI memory and spatial computing.

This server implements the Model Context Protocol (MCP), exposing a comprehensive suite of tools for geometrical data analysis, graph traversal, and cognitive AI metrics directly to models in Claude Desktop, Cursor, and other MCP hosts.

🚀 Key Features

1. Geometric Data Diagnostics

Identify the optimal geometry for your data using Gromov Delta-hyperbolicity analysis.

  • hyperspace_analyze_geometry: Uses the 4-point condition to recommend Lorentz, Poincare, Cosine, or L2 metrics for your datasets.

2. Cognitive AI Tools (Agentic Logic)

Track and manage the model's internal reasoning stability.

  • hyperspace_analyze_thought_stability: Calculates Lyapunov Convergence of a trajectory (Chain of Thought). Detects if a model is "hallucinating" or converging on a stable logical attractor.
  • hyperspace_find_clusters: Detects emergent semantic regions in the database knowledge graph to help the model synthesize higher-level concepts.

3. High-Performance Knowledge Retrieval

  • hyperspace_search_text: Natural language semantic search using server-side embeddings.
  • hyperspace_search_wasserstein: Optimal Transport (OT) based search for comparing complex distributions and finding non-obvious conceptual overlaps.
  • hyperspace_insert_text: Asynchronous storage of factual claims or system logs with automatic vectorization.

4. Graph Memory Navigation

  • hyperspace_graph_traverse: Perform deep BFS/DFS traversal through the HNSW knowledge graph. Allows the model to "follow paths" between disparate facts to build complex reasoning chains.

🛠️ Installation & Setup

Prerequisites

  • Node.js 18+
  • Running instance of HyperspaceDB (default: localhost:50051)

1. Run directly with npx (Recommended)

You don't need to install anything. Just run:

npx mcp-hyperspacedb

2. Configuration for MCP Hosts

Add the following to your MCP configuration file (e.g., claude_desktop_config.json or Cursor settings):

{
  "mcpServers": {
    "hyperspacedb": {
      "command": "npx",
      "args": ["-y", "mcp-hyperspacedb"],
      "env": {
        "HYPERSPACE_HOST": "localhost:50051",
        "HYPERSPACE_API_KEY": "I_LOVE_HYPERSPACEDB"
      }
    }
  }
}

🧩 Available Tools

Data Tools

  • hyperspace_list_collections: Get all active collections.
  • hyperspace_create_collection: Setup new memory spaces with specific geometry.
  • hyperspace_insert_text: Store new facts into the DB.
  • hyperspace_search_text: Query the DB using semantic similarity.
  • hyperspace_search_wasserstein: Advanced cross-feature distribution search.

Graph & AI Tools

  • hyperspace_get_neighbors: Explore local connectivity in the vector graph.
  • hyperspace_graph_traverse: Perform multi-hop logical exploration.
  • hyperspace_find_clusters: Identify thematic regions in vector space.
  • hyperspace_analyze_thought_stability: Validate Chain of Thought (CoT) stability.
  • hyperspace_analyze_geometry: Run Gromov Delta analysis on raw vectors.

System Tools

  • hyperspace_get_stats: Telemetry on cluster health, clocks, and vector volume.
  • hyperspace_trigger_reconsolidation: Manually trigger "AI Sleep Mode" (Flow Matching optimization) for a collection.

👨‍💻 Development

To run in development mode with live logs:

npm run dev

📜 License

MIT