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Holographic Memory MCP

Persistent local memory for AI agents through the Model Context Protocol. The server stores memories on your machine and supports stdio and streamable HTTP transports.

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Run

Python 3.9 or newer is required for this launcher. Run it directly with uvx:

uvx holographic-memory-mcp

The default stdio transport works with MCP clients that launch a local command. To share one server between clients, use streamable HTTP:

uvx holographic-memory-mcp --transport http

The HTTP endpoint defaults to http://127.0.0.1:8765/mcp. See the MCP guide for client configuration, storage locations, encryption, authentication, and available flags.

What the server provides

Tool Purpose
remember Save or update a memory.
recall Find memories relevant to a query.
search Search with explicit filters and ranking options.
get, list Read one memory or page through a store.
forget Delete selected memories.
stats, export Inspect and export a store.

The server also exposes memory resources and prompts. Memories persist across client sessions. By default, recall uses lexical search; semantic recall requires a build configured with a local embedding model.

Launcher and binary

The package installs a small Python launcher. On first run, it downloads the matching prebuilt hms-mcp binary from the GitHub release and verifies its SHA-256 against a checksum table shipped in the package. The server itself runs locally; the launcher needs network access for that first binary download.

Set HMS_MCP_BINARY to run your own hms-mcp build. HMS_MCP_CACHE_DIR changes the download cache. The MCP guide covers the server's HMS_MCP_* configuration variables.

The same launcher is available on npm.

Metadata

Release files for holographic-memory-mcp 0.1.1

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