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Shodh Memory MCP server

by varun29ankuS·io.github.varun29ankuS/shodh-memory·v0.2.0·294 stars

Cognitive memory for AI agents — semantic search, Hebbian learning, knowledge graphs.

C68/100grade C
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Shodh Memory tools (38, 8 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • add_projectwrite action

    Create a new project to group todos. Use parent to create a sub-project under another project.

  • add_todo

    Add a task to your todo list. Supports GTD workflow with projects, contexts (@computer, @phone), priorities, due dates, and subtasks (via parent_id).

  • add_todo_comment

    Add a comment to a todo. Use to track progress, notes, or resolution details.

  • archive_project

    Archive a project. Archived projects are hidden by default but can be restored.

  • backup_createwrite action

    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_purge

    Purge old backups, keeping only the most recent N. Useful for managing disk space.

  • backup_restore

    Restore a previously created backup by ID. This replaces all current data for the user with the backup contents. Server restart is recommended after restore.

  • backup_verify

    Verify backup integrity using SHA-256 checksum. Use to check if a backup is corrupted before restoring.

  • complete_todo

    Mark a todo as complete. For recurring tasks, automatically creates the next occurrence.

  • consolidation_report

    Get a report of what the memory system has been learning. Shows memory strengthening/decay events, edge formation, fact extraction, and maintenance cycles. Use this to understand how your memories are evolving.

  • 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.

  • delete_projectwrite action

    Permanently delete a project. Use delete_todos=true to also delete all todos in the project.

  • delete_todowrite action

    Delete a todo permanently.

  • delete_todo_commentwrite action

    Delete a comment from a todo.

  • dismiss_reminder

    Dismiss/acknowledge a triggered reminder. Call this after you've handled a reminder.

  • forgetwrite action

    Delete a specific memory by ID

  • list_memories

    List all stored memories

  • list_projects

    List all projects with todo counts and status breakdown.

  • list_reminders

    List all pending reminders. Use to check what reminders are scheduled.

  • list_subtasks

    List subtasks of a parent todo. Use add_todo with parent_id to create subtasks.

  • list_todo_comments

    List all comments and activity history for a specific todo.

  • list_todos

    List or search todos. Supports semantic search via query parameter, or GTD-style filtering. Returns Linear-style formatted output grouped by status.

  • memory_stats

    Get statistics about stored memories

  • proactive_context

    REQUIRED: Call this tool with EVERY user message to surface relevant memories and build conversation history. Pass the user's message as context. This enables: (1) retrieving memories relevant to what the user is asking, (2) building persistent memory of the conversation for future sessions. The system analyzes entities, semantic similarity, and recency to find contextually appropriate memories. A

  • read_memory

    Read the FULL content of a specific memory by ID. Use this when you need to see the complete text of a memory that was truncated in search results.

  • recall

    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 lear

  • 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').

  • remember

    Store a memory for future recall. Use this to remember important information, decisions, user preferences, project context, or anything you want to recall later.

  • reorder_todo

    Move a todo up or down within its status group. Use to prioritize tasks manually.

  • repair_index

    Repair vector index by re-indexing orphaned memories. Use this when verify_index shows unhealthy status. Returns count of repaired memories.

  • reset_token_session

    Reset the token counter for a new session. Call this when starting a new conversation or after context has been compressed/summarized.

  • set_reminder

    Set a reminder for the future. Triggers on time (at specific time or after duration) or context match (when keywords appear in conversation). Reminders will surface automatically when conditions are met.

  • todo_stats

    Get statistics about your todos - counts by status, overdue items, etc.

  • token_status

    Get current token usage status for this session. Returns tokens used, budget remaining, and percentage consumed. Use this to check context window health.

  • update_todowrite action

    Update a todo's properties. Use short ID prefix (e.g., SHO-1a2b) or full ID.

  • update_todo_commentwrite action

    Update an existing comment on a todo.

  • verify_index

    Verify vector index integrity - diagnose orphaned memories that are stored but not searchable. Returns health status and count of orphaned memories.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

2 medium
  • Code scan2 source files scanned15/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 1 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Findings (2)

  • mediumnpm install lifecycle script presentinstall.script
  • mediumnpm install lifecycle script presentinstall.script
    package.json: …coverage": "vitest run --coverage", "postinstall": "node scripts/postinstall.cjs", "pr…
Overall 68/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

Install Shodh Memory in Claude Code, Cursor or VS Code

Runs npx -y @shodh/memory-mcp on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add shodh-memory -- npx -y @shodh/memory-mcp
Add to Cursor

What the publisher says

From the Shodh Memory repository's README, as published. We do not edit it. Read it on GitHub

Shodh-Memory

Persistent cognitive memory for AI agents and robots — with no LLM in the loop. Remembers what matters, forgets what doesn't, gets smarter with use.

AI agents forget everything between sessions. Robots lose context between missions. They repeat mistakes, miss patterns, and treat every interaction like the first one.

Shodh-Memory fixes this. It's persistent memory that actually learns — memories you use often become easier to find, old irrelevant context fades automatically, and recalling one thing brings back related things. Works for chat agents (MCP/HTTP), robots (Zenoh/ROS2), and edge devices. No API keys. No cloud. No external databases. No LLM in the loop. One binary.

Why Not Just Use mem0 / Cognee / Zep?

Every other memory system delegates intelligence to LLM API calls — that's why they're slow, expensive, and can't work offline.

No LLM in the Loop

Storing a memory makes zero LLM calls. Recalling makes zero LLM calls. Entity extraction, relation typing, knowledge-graph construction, causal tracing, ranking, decay, consolidation — all of it runs locally as algorithms, not API round-trips:

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Shodh Memory: common questions

Is Shodh Memory MCP server safe?
With care: it is graded C, so read the findings first (68/100). Read the Shodh Memory safety report
How do I install Shodh Memory?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Shodh Memory need an API key?
Yes. The registry entry asks for SHODH_API_KEY.
Is Shodh Memory maintained?
The last commit was in the last day (2026-09-27). The latest release is v0.2.0.
What can I use instead of Shodh Memory?
Servers from other publishers that do the same job: Octocode MCP server, Reverie MCP server and Codeseeker MCP server. Compare all Shodh Memory alternatives.

Alternatives to Shodh Memory

Same job from other publishers: the closest match first, then the best rated.

All Shodh Memory alternatives →
  • Octocode
    AI-powered code indexer with semantic search and knowledge graphs
    A
  • Reverie
    Graph memory that dreams: Neo4j knowledge-graph memory for AI agents with hybrid search
    B
  • Codeseeker
    Graph-powered code intelligence with semantic search and knowledge graph for AI assistants
    C
  • Socraticode
    MCP server for enterprise local codebase indexing, semantic search, and code dependency graphs.
    B
  • Sui Knowledge Base (kapa.ai)
    Semantic search across Sui documentation and knowledge sources, powered by kapa.ai
    A

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