In-depth architectural comparison of the Simplemem and Shodh Memory MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Simplemem
Knowledge & Memory · Local stdio
Quality: 39/100 (Fair) | Auth: No auth required
Shodh Memory
Knowledge & Memory · Local stdio
Quality: 69/100 (Great) | Auth: No auth required
Verdict Summary: Choose Simplemem if you need specialized Knowledge & Memory tools running via a local process. Choose Shodh Memory if your workspace requires Knowledge & Memory integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Simplemem when:
You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Store a memory for future recall. Use this to remember important information, decisions, user preferences, project context, or anything you want to recall later.
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Simplemem is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Shodh Memory belongs to Knowledge & Memory using local stdio subprocess. Select Simplemem when you need capabilities focused on knowledge & memory and Shodh Memory when you require tools for knowledge & memory.
Search memories AND todos using semantic similarity. Returns both relevant memories and matching todos. Use this to find past experiences, decisions, context, or pending work. Modes: 'semantic' (vector similarity), 'associative' (graph traversal), 'temporal' (time-based retrieval), 'hybrid' (combined), 'spatial' (geo-location based), 'mission' (mission context), 'action_outcome' (reward-based learning).
recall_by_tags
Find memories by tags. Returns memories matching ANY of the provided tags. Useful for finding memories by category (e.g., 'tool:Edit', 'file:src/main.rs', 'source:hook', 'error', 'session-summary').
context_summary
Get a condensed summary of recent learnings, decisions, and context. Use this at the start of a session to quickly understand what you've learned before.
list_memories
List all stored memories
forget
Delete a specific memory by ID
memory_stats
Get statistics about stored memories
verify_index
Verify vector index integrity - diagnose orphaned memories that are stored but not searchable. Returns health status and count of orphaned memories.
repair_index
Repair vector index by re-indexing orphaned memories. Use this when verify_index shows unhealthy status. Returns count of repaired memories.
backup_create
Create a backup of all memories. Returns backup metadata including ID, size, and checksum. Backups are stored locally and can be restored later.
backup_list
List all available backups for this user. Returns backup history with IDs, timestamps, and sizes.
backup_verify
Verify backup integrity using SHA-256 checksum. Use to check if a backup is corrupted before restoring.