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Local-first AI memory MCP server. Record, recall and consolidate memory on your own machine.
About
Local-first AI memory MCP server. Record, recall and consolidate memory on your own machine.
Security Report
4 tools verified · Open access · No issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Remote servers are capped at 8.0 because source code is not available for review. The score reflects endpoint verification only.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-qianqiuwanzi-hypermarrow-mcp": {
"args": [
"-y",
"hypermarrow-mcp"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub 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 preferencerecall_memory– retrieve the most relevant past contextconsolidate– merge duplicates and age out stale entriesfile_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
- Homepage: https://hm.qianshi.cool/
- Company: 千视科技 (qianshi.cool)
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.
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