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hypermarrow-mcp

hypermarrow-mcp

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hm.qianshi.coolMemory & Knowledge0Updated 5w ago
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About hypermarrow-mcp

hypermarrow-mcp is a local-first memory layer for MCP-compatible clients, aimed at keeping durable context on the user's machine. It provides tools to record, retrieve, and consolidate memories, with optional use of a configured backend.

Key features

  1. 01Record decisions, facts, and preferences
  2. 02Retrieve relevant past context
  3. 03Merge duplicates and retire stale entries
  4. 04Map short names to local file paths
  5. 05Store memory locally by default

Use cases

  1. 01Keep durable context between AI sessions
  2. 02Recall earlier decisions and preferences
  3. 03Consolidate accumulated memory entries

MCP support

Exposes memory tools to MCP-compatible clients over stdio. Memory is stored locally unless a user-configured HYPERMARROW_ENDPOINT is set.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "qianqiuwanzi-hypermarrow": {
      "command": "npx",
      "args": [
        "-y",
        "hypermarrow-mcp"
      ]
    }
  }
}
Run commandnpx -y hypermarrow-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmhypermarrow-mcp0.1.1

Tools

4

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
tagsarrayNoOptional tags for later filtering.
contextstringYesThe text to remember.

Details

From the project README

HyperMarrow MCP Server

Local-first AI memory layer for the Model Context Protocol.

hypermarrow-mcp lets any MCP-compatible client read and write your long-term memory:

  • record_context – remember a decision, fact, or preference
  • recall_memory – retrieve the most relevant past context
  • consolidate – merge duplicates and age out stale entries
  • file_anchor – map a short name to a local file path

All memory lives under ~/.hypermarrow/memory.json on your own machine. Nothing is sent to the cloud unless you explicitly set HYPERMARROW_ENDPOINT to your own backend.

Install

npx -y hypermarrow-mcp

Or add to your MCP client config:

{
  "mcpServers": {
    "hypermarrow": {
      "command": "npx",
      "args": ["-y", "hypermarrow-mcp"]
    }
  }
}

Product

Privacy

Memory data is stored locally. The server only talks to the client over stdio and, optionally, to a user-configured HYPERMARROW_ENDPOINT. No telemetry, no cloud sync by default.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.