Skip to main content
Glama
putervision

state-memory-mcp

by putervision
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to state-memory-mcp

No user-submitted related servers found.

    Related Servers

    • Mono Memory MCP

      potato-castle
      A
      license
      Not graded
      quality
      D
      maintenance
      A self-hosted MCP server that provides AI assistants with a shared, persistent SQLite-backed memory for storing and retrieving project context, decisions, and discoveries. It enables cross-session continuity and team-wide knowledge sharing to keep AI coding tools aligned and informed.
      3
      MIT

    • Project Brain

      myczh-1
      A
      license
      Not graded
      quality
      D
      maintenance
      A local MCP memory server that gives AI assistants durable project memory across coding sessions, storing context, changes, and decisions.
      2 npm
      1
      MIT

    • AIVectorMemory

      Edlineas
      A
      license
      B
      quality
      D
      maintenance
      MCP server that provides cross-session persistent memory for AI coding assistants using local vector database and semantic search, enabling automatic recall of project context, issues, and tasks.
      9
      127 PyPI
      91
      Apache 2.0

    • Ramorie

      kutbudev
      A
      license
      Not graded
      quality
      B
      maintenance
      Persistent project memory and task management for AI coding agents through MCP. Lets Claude Code, Cursor, Codex and other MCP clients save decisions and bug fixes, search relevant context, and reuse it across sessions.
      1
      MIT

    • Sugar

      Sitas17424
      F
      license
      Not graded
      quality
      A
      maintenance
      A local-first MCP memory server that lets AI coding agents store, search, and recall project-specific and cross-project knowledge, so architecture decisions, preferences, error patterns, and coding guidelines persist across sessions. It also exposes optional task-queue tools for handing off autonomous work that draws on the same stored context.
      -
    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    A3.7/5.0

    Scored across 13 tools

    Disambiguation3/5

    The descriptions are unusually thorough with explicit 'use X instead of Y' guidance, which genuinely helps separate tools like manage_nodes vs manage_edges vs use_blackboard and manage_snapshots vs manage_database vs get_events. However, the underlying domain heavily overlaps: nodes/edges/specs/blackboard all manipulate graph-like entities, and query_graph/get_analytics/run_diagnostics all operate on the same graph for read, aggregate, and maintenance purposes. Boundaries are clarified by prose rather than being intrinsically clean.

    Naming Consistency3/5

    Most tools use a manage_* pattern (manage_data, manage_nodes, manage_edges, manage_sessions, manage_tasks, manage_snapshots, manage_specs, manage_database), which is consistent. But the remaining tools break the pattern with distinct verbs (query_graph, get_analytics, get_events, run_diagnostics, use_blackboard), producing mixed conventions. It remains readable, but there is no single predictable verb_noun scheme.

    Tool Count4/5

    13 tools is within the well-scoped range and appropriate for a state/memory graph server covering graph, tasks, sessions, specs, analytics, events, and diagnostics. The design consolidates many operations as actions within each tool rather than exploding the tool count, keeping the surface manageable. Slightly heavy given the breadth, but reasonable.

    Completeness4/5

    Coverage is broad: node/edge CRUD, task workflow, sessions, snapshots/time-travel, specs, database maintenance, graph queries, analytics, event ledger, diagnostics, and multi-agent blackboard. Most lifecycle operations (create, update, get, list, remove, batch) appear across the mutation tools. Minor gaps exist, such as bulk-delete actions being less explicit than bulk-create.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources