State Memory MCP

Official registry AI and agents

Persistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.

What can you do with State Memory MCP?

  • 🧠 Deterministic State Memory & Compact TaskSlices: Zero LLM in the loop for memory operations; fast, deterministic SQLite graph traversals, and sub-1KB TaskSlice extraction for System 1 fast path evaluation.
  • ⚡ 13 Production-Grade Consolidated MCP Tools: Full CRUD, relationship linking, DAG cycle checks, FTS5 search, TF-IDF RAG, time-travel history rollback, Spec-Driven Development, and auto-healing validation.
  • 📉 Efficient Context Management & Decision Thresholding: Offloads context to a local SQLite database, filters sub-0.70 routine decisions to append-only event logs to prevent graph bloat, and preserves high-significance turns.
  • 🚀 67%–74% Latency Reduction: Eliminates multi-step file scanning loops; agents retrieve unblocked tasks and blockers in milliseconds.
  • 🤝 Multi-Agent Blackboard: Shared Context Store allowing parallel subagents to publish decisions, tasks, and blocker updates safely.
  • 🎨 Interactive 3D Visualizer: Browser-based dark-mode 3D WebGL force-directed graph visualizer (state-memory-mcp view).
  • 🔗 Dual-MCP Synergy: Pair with @putervision/vision-memory-mcp for visual state caching, perceptual hashing, and cryptographic multimodal evidence packs.
  • 🛡️ 100% Local & Private: Local-first architecture; all state stays inside .state-memory-mcp/ in your workspace.

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

NPM package @putervision/state-memory-mcp
Claude Code
claude mcp add state-memory-mcp -- npx -y @putervision/state-memory-mcp@1.4.1
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "state-memory-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "@putervision/state-memory-mcp@1.4.1"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. @putervision/state-memory-mcp
  2. ⚡ Quick Start & Installation
  3. 🌟 Key Highlights
  4. 🛠️ MCP Tool Suite
  5. 🚀 Architecture & State Graph Lifecycle
  6. 📚 Documentation Directory
  7. 📖 Agent Playbook: 5-Step Canonical Workflow
  8. 🧪 Testing
  9. ⚖️ License & Disclaimers

@putervision/state-memory-mcp

@putervision/state-memory-mcp is a zero-infrastructure, deterministic Model Context Protocol (MCP) server that provides AI coding assistants (such as Cursor, Claude Code, Gemini, or Copilot) with a structured, persistent SQLite graph for tracking workflow state—tasks, decisions, artifacts, plans, blockers, and their semantic relationships.

🌐 Official Documentation & Website: statememorymcp.com


⚡ Quick Start & Installation

Prerequisites: Node.js >= 18.18.0

# 1. Install globally
npm install -g @putervision/state-memory-mcp

# 2. Navigate to your project directory
cd your-project

# 3. Initialize state-memory-mcp
# Creates .state-memory-mcp/, updates .gitignore, registers project,
# and scaffolds IDE instructions and MCP configs for Cursor, Claude, VS Code, Windsurf, etc.
state-memory-mcp init

# Done! Restart your IDE or Agent Manager to activate.
Alternative Options
# Run directly via binary (after global install)
state-memory-mcp run

# Re-initialize across all registered workspace projects
state-memory-mcp init-global

🌟 Key Highlights

  • 🧠 Deterministic State Memory & Compact TaskSlices: Zero LLM in the loop for memory operations; fast, deterministic SQLite graph traversals, and sub-1KB TaskSlice extraction for System 1 fast path evaluation.
  • ⚡ 13 Production-Grade Consolidated MCP Tools: Full CRUD, relationship linking, DAG cycle checks, FTS5 search, TF-IDF RAG, time-travel history rollback, Spec-Driven Development, and auto-healing validation.
  • 📉 Efficient Context Management & Decision Thresholding: Offloads context to a local SQLite database, filters sub-0.70 routine decisions to append-only event logs to prevent graph bloat, and preserves high-significance turns.
  • 🚀 67%–74% Latency Reduction: Eliminates multi-step file scanning loops; agents retrieve unblocked tasks and blockers in milliseconds.
  • 🤝 Multi-Agent Blackboard: Shared Context Store allowing parallel subagents to publish decisions, tasks, and blocker updates safely.
  • 🎨 Interactive 3D Visualizer: Browser-based dark-mode 3D WebGL force-directed graph visualizer (state-memory-mcp view).
  • 🔗 Dual-MCP Synergy: Pair with @putervision/vision-memory-mcp for visual state caching, perceptual hashing, and cryptographic multimodal evidence packs.
  • 🛡️ 100% Local & Private: Local-first architecture; all state stays inside .state-memory-mcp/ in your workspace.

🛠️ MCP Tool Suite

@putervision/state-memory-mcp provides 13 production-grade consolidated MCP tools organized across 5 core workflow domains:

  • Graph & Relationships: manage_nodes (node CRUD, FTS5/TF-IDF vector search, atomic batch mutations, observation notes, thresholded fast decision logging), manage_edges (typed DAG links, multimodal visual state linking).
  • Task Execution & Work Queue: manage_tasks (topological dependency queue, blocker detection, task completion with artifacts, auto-prune), manage_sessions (agent attribution, turn tracking, context bootstrap).
  • Spec-Driven Development (SDD): manage_specs (PRD/RFC parsing, requirement-to-task decomposition, live acceptance criteria verification, compliance scoring).
  • Analytics, Audit & Diagnostics: get_analytics (velocity, burndown, token ROI, cognitive load, critical path), get_events (SHA-256 tamper-evident event ledger), run_diagnostics (DAG validation, health checks, AST reference integrity).
  • Data, Snapshots & Multi-Agent: manage_snapshots (checkpoints, time-travel undo), manage_database (backups, checksum audits, VCS branch merge), manage_data (bulk import/export, ML trajectories with interleaved fast decision events), query_graph (subgraphs, dependency tracing, raw SQL, sub-1KB compact_slice), use_blackboard (multi-agent asynchronous topic board).

👉 For complete parameter specifications, return schemas, and example payloads, see the Tools Reference Guide and Formal API Reference.


🚀 Architecture & State Graph Lifecycle

                      AI Agent Prompt / Task
                                │
                                ▼
               ┌─────────────────────────────────┐
               │  Agent Session Attribution       │ ──▶ manage_sessions(action: "start")
               └────────────────┬────────────────┘
                                │
                                ▼
               ┌─────────────────────────────────┐
               │  Context & Task Prioritization   │ ──▶ get_analytics(action: "summary")
               │                                 │ ──▶ manage_tasks(action: "next")
               └────────────────┬────────────────┘
                                │
                                ▼
               ┌─────────────────────────────────┐
               │  Deterministic Graph Mutation   │ ──▶ manage_nodes(action: "create"|"update")
               │  (Tasks, Decisions, Blockers)   │ ──▶ manage_edges(action: "add"|"link_visual")
               └────────────────┬────────────────┘
                                │
                                ▼
               ┌─────────────────────────────────┐
               │  Spec & Integrity Verification  │ ──▶ manage_specs(action: "compliance"|"verify")
               │                                 │ ──▶ run_diagnostics(action: "validate")
               └────────────────┬────────────────┘
                                │
                                ▼
               ┌─────────────────────────────────┐
               │  Persistent SQLite Storage      │ ──▶ .state-memory-mcp/graph.db (WAL mode)
               │  Append-Only Event Ledger       │ ──▶ SHA-256 Cryptographic Audit Chain
               └─────────────────────────────────┘

📚 Documentation Directory

Explore dedicated guides and deep dives in the docs/ directory:

GuideDescription
🏗️ Architecture & Codebase DistillationHigh-signal architectural overview, module inventory, data flows, and design decisions.
🚀 v0.10 → v1.0 Migration GuideStep-by-step migration guide, legacy tool mapping table, and STATE_MEMORY_COMPAT mode.
💡 Value Proposition & TheoryCognitive Externalization, FSM Formalism, First-Hop Determinism & Benchmark metrics.
📋 State Memory ConceptsNode Types (task, decision, blocker...), Status Values, Typed Edges & Seeding Guidelines.
⚙️ Configuration & IDE SetupAuto-Initialization details, Environment Variables table, and Editor Configs (Cursor, VS Code, Claude, Antigravity, Windsurf).
🛠️ CLI Command ReferenceCLI flags (init, run, view, inspect, metrics, audit, doctor, backup, restore, merge) & Git Scanner.
⏱️ Sessions, Snapshots & SDDSession Lifecycle, Event Audit Trail, Snapshots, Trajectories, Sub-directory support & Spec-Driven Development.
🧰 Tools, Resources & PromptsComplete reference for all 13 Consolidated MCP Tools, read-only state-memory:/// Resources, and Prompt templates.
📘 Formal API ReferenceFormal parameters, return schemas, and code signatures for all MCP endpoints.
🎨 3D Visualizer GuideViewing and exporting the interactive WebGL 3D Force-Directed Graph visualizer.
🗄️ Database SchemaSQLite tables, columns, indexes, and schema migration history.

📖 Agent Playbook: 5-Step Canonical Workflow

When an autonomous AI agent enters a repository with state-memory-mcp:

1. Orient & Bootstrap ──▶ manage_sessions(action: "start") + get_analytics(action: "summary")
2. Task Selection     ──▶ manage_tasks(action: "next") + manage_tasks(action: "find_blockers")
3. Trace Context      ──▶ query_graph(action: "trace") + manage_specs(action: "compliance")
4. Execute & Record   ──▶ manage_nodes(action: "create", type: "decision") + manage_edges(action: "link_visual")
5. Validate & Close   ──▶ run_diagnostics(action: "validate") + manage_tasks(action: "complete") + manage_sessions(action: "end")

🧪 Testing

# Run full unit, integration, and performance benchmark test suite across all 113 test files (418 tests)
npm run test

⚖️ License & Disclaimers

Developed and maintained by PuterVision. Released under the MIT License.

  • Local Storage Guarantee: All graph data, decision records, and event logs remain 100% local in your workspace. No telemetry or project data is ever transmitted.
  • Trademarks & Non-Affiliation: Product names (Cursor, Claude Code, Gemini, Windsurf, VS Code, GitHub, SQLite) are property of their respective owners and used solely for compatibility identification.

Frequently asked questions

What is State Memory MCP?

Persistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.

How do I install State Memory MCP?

It runs on your machine. In Claude Code: claude mcp add state-memory-mcp -- npx -y @putervision/state-memory-mcp@1.4.1. For other clients, paste the JSON configuration from this page into their MCP settings.

Does State Memory MCP need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is State Memory MCP open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains State Memory MCP?

It is published by putervision. AI.tn lists it but does not maintain or endorse it.

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