Skip to main content
Glama
00face

Lwa MCP

by 00face
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to Lwa MCP

No user-submitted related servers found.

    Related Servers

    • craft

      wdx9413
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to index and search local skill libraries, persist and resume task checkpoints, and run validated workflow plans with controlled approval and write permissions.
      MIT

    • EdgeRoute

      Kedar7412
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents and IDEs to classify developer intent locally in under 2 milliseconds, executing tools instantly when confident and abstaining to a cloud LLM when uncertain. It also logs outcomes to a private on-device replay buffer for continuous fine-tuning and reports lifetime token, latency, and cost savings.
      1
      MIT

    • genpark-jev-system1

      Alpha-Park
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to resolve routine typed routing, loop-stall arbitration, and tool safety checks locally instead of invoking a frontier LLM, returning schema-enforced decision outputs and telemetry at sub-millisecond latency. Also provides reversible execution checkpoints, token budgets, and decay-based episodic memory for safe, privacy-preserving autonomous operation.
      7
      MIT
    • Via by Vektor-Memory

      Viaofficial

      Vektor-Memory
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables routing context and execution across AI tools like Claude, Cursor, Windsurf, and ChatGPT with a shared memory, task board, and context bus, plus local file conversion.
      7 npm
      9
      Apache 2.0

    • genpark-personal-agent-dual

      Alpha-Park
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables personal AI agents to route routine, reflexive decisions through fast deterministic System-1 cognition while reserving frontier LLM calls for ambiguous multi-hop plans. Combines ambient perception, decayed episodic memory with contradiction resolution, and proactive sensing behind reversible execution checkpoints, token budgets, and local-first memory retention.
      7
      MIT
    Deploy Server
    Context Every Agent Can ShareAgents share what they learn, hand off work, and keep it when you switch models. Start with 5 GB free.fulcradynamics.comAd

    TDQS

    C2.4/5.0

    Scored across 40 tools

    Disambiguation2/5

    Several tools occupy the same prepare/lock/run lifecycle—prepare_task, route_task, smart_complete, answer_query, quick_response, verify_work, plan_work, and confirm_and_run—so an agent can easily select the wrong one. The deprecated confirm_and_run alias and legacy smart_complete name add further ambiguity despite descriptions attempting to differentiate them.

    Naming Consistency3/5

    Most tools use snake_case verb_noun names, but there are noun-only status tools (pipeline_status, router_status, model_tiers, library_status), a resource noun (syntax_contract_resource), and legacy/multi-verb names (smart_complete, confirm_and_run). The convention is readable but not consistently applied.

    Tool Count2/5

    40 tools is far beyond the comfortable MCP range, and many are granular variants of the same prepare-before-run flow. The broad domain explains some of the count, but the set would be tighter if the shared execution path were factored into fewer tools.

    Completeness3/5

    The lifecycle is broadly covered: task preparation/approval/execution, library tool management, provider refresh, and workflow analysis. However, library tools lack update/delete operations and several prepared actions depend on a generic run_prepared_task, leaving some gaps in the apparent CRUD surface.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources