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moltizmo
by moltizmo

Smriti

Local-first persistent memory for AI agents via MCP.

Smriti (स्मृति) — Sanskrit for "memory, remembrance"

One brain. Every agent. Zero cloud. Zero cost.

What is this?

A standalone MCP server backed by sqlite-vec and a local embedding model. Install it, point any MCP-compatible agent at it, and every AI you use shares one persistent, semantically searchable memory.

Smriti

Cloud alternatives

Setup

npx smriti

Accounts + API keys + config

Cost

$0

Variable

Privacy

100% local

Data on external servers

Offline

Full functionality

Needs internet

Portability

Single .db file

DB export/migration

Related MCP server: OmniHub

Install

npm install -g smriti

Usage

# MCP server — stdio mode (for Claude Code, Cursor, etc.)
smriti

# MCP server — HTTP mode (for remote agents)
smriti --http --port 3838

CLI Quick Reference

# Capture a memory
smriti capture "We chose PostgreSQL over MySQL for the new service"

# Semantic search
smriti search "database decisions"

# Browse recent memories (last 7 days)
smriti recall --days 7

# Browse by topic
smriti recall "authentication"

# Batch-extract memories from a conversation or document
smriti ingest --text "Long meeting notes or conversation log..." --threshold 0.4

# Memory stats
smriti stats

# Sync to GitHub (requires: smriti auth)
smriti sync

# GitHub auth
smriti auth
smriti whoami
smriti logout

MCP Client Configuration

Claude Code

Add to ~/.claude/mcp.json:

{
  "mcpServers": {
    "memory": {
      "command": "smriti"
    }
  }
}

Cursor

Add to MCP settings:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["smriti"]
    }
  }
}

Any MCP client (HTTP mode)

smriti --http --port 3838

Then point your client at http://localhost:3838/mcp.

Tools

Tool

Description

capture

Store a thought with auto-extracted metadata

search

Semantic search — find thoughts by meaning

recall

Browse recent memories with filters

forget

Delete a specific memory by ID

context

Get structured context bundle for a topic

stats

Memory patterns and insights

Resources

URI

Description

memory://recent

Last 24h of thoughts

memory://topics

Topic index with counts

memory://people

People mentioned + context

memory://stats

Overall memory statistics

Prompts

Name

Description

brain-dump

Guided capture session

weekly-review

End-of-week synthesis

migrate

Import memories from other sources

Configuration

Config lives at ~/.smriti/config.json:

{
  "db_path": "~/.smriti/brain.db",
  "embedding": {
    "provider": "onnx",
    "model": "Xenova/all-MiniLM-L6-v2"
  },
  "extraction": {
    "provider": "rules"
  },
  "server": {
    "transport": "stdio",
    "port": 3838
  }
}

How it works

  1. You (or an agent) call capture with text

  2. Smriti generates a vector embedding locally (all-MiniLM-L6-v2 via ONNX)

  3. Regex-based extraction pulls out people, topics, actions, and classifies the type

  4. Everything is stored in a single SQLite file with sqlite-vec for vector search

  5. search finds thoughts by semantic similarity, not just keywords

  6. All data stays on your machine — nothing leaves localhost

License

MIT

A
license - permissive license
-
quality - not tested
D
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

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