Skip to main content
Glama
MnemeHQ

Mneme Decision MCP

Official
by MnemeHQ
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to Mneme Decision MCP

No user-submitted related servers found.

    Related Servers

    • trailstone

      VishwamDhavale
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to read and update a repository's decision ledger, check which files a decision governs, find stale files after a decision reversal, and record or reverse decisions over MCP.
      511 npm
      Apache 2.0

    • loopgrid-mcp

      loopgridio
      A
      license
      A
      quality
      B
      maintenance
      Enables MCP-compatible hosts to record, retrieve, and verify LoopGrid decision evidence through tools for decisions, reviews, actions, outcomes, and verification.
      6
      19 PyPI
      Apache 2.0

    • arra-memory-lab

      Soul-Brews-Studio
      F
      license
      Not graded
      quality
      B
      maintenance
      Enables trustworthy AI memory operations including authoritative memory creation, hybrid recall with provenance, evidence tracking, and safe dry-run-first forget and rebuild operations through a stateless MCP endpoint.
      2
      -

    • SYUNE

      Npalyan002
      A
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP hosts and applications to give AI agents governed persistent memory and bounded context with authorization, provenance, temporal/version control, lifecycle, audit, and optional provider-agnostic model execution.
      Apache 2.0
    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

    A4.7/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool targets a distinct action-resource pair: propose/propose_batch differ only in cardinality and cross-reference each other, while get/search/applicable_to/trace are clearly separated by input type (stable id vs text vs context/path vs provenance). No two tools would be confused for the same operation.

    Naming Consistency5/5

    All tools share the decision.* namespace and use short, imperative verbs (propose, get, search, trace). The two compound names (propose_batch, applicable_to) use the same underscore convention, so the naming feels systematic and predictable.

    Tool Count5/5

    Six tools is a tight, purposeful surface for a decision index: two write paths (single/batch), three read/retrieval paths (by id, text search, context overlap), and one provenance trace. Each tool has a distinct role and none feels redundant.

    Completeness4/5

    The core write-once proposal plus retrieval workflow is well covered, including batch submission and lineage tracing. However, there is no way to update, withdraw, or transition a proposal's status within the MCP; this is explicitly delegated to external human authority, but agents still cannot correct or retire a mistaken proposal.

    Maintenance

    ActivityActive
    ResponsivenessResponsive

    Resources