Skip to main content
Glama
cerebrochain-mcp-server

cerebrochain-mcp-server

by CerebroChain

Related Servers

Alternatives to cerebrochain-mcp-server

No user-submitted related servers found.

    Related Servers

    • A
      license
      A
      quality
      B
      maintenance
      Enables autonomous multi-agent logistics operations through MCP tools, resources, and prompts for routing, inventory, cargo inspection, disruption recovery, and conversational dispatch. It supports both modern and legacy MCP specs over stdio and HTTP, including secure API and feedback-optimized workflows.
      5
      1
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Ocean container shipping intelligence for AI agents — D\&D tariffs, freight rates, vessel schedules, port congestion, inland haulage across 6 major carriers. 24 MCP tools.
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to forecast SKU sales velocity, calculate safety stock and reorder points, and autonomously generate supplier purchase orders when stock is running low. It exposes this supply-chain analysis over JSON-RPC 2.0 tools that can be called from any MCP-compatible client.
      7
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI assistants to query and manage logistics shipment data, supporting operations like tracking, quoting, and performance analysis via nine tools backed by a demo dataset or a REST API.
      9
      253 npm
      MIT

    TDQS

    A3.5/5.0

    Scored across 20 tools

    Disambiguation3/5

    Most tools have distinct purposes (e.g., check_stock_levels vs lookup_sku vs search_inventory target different access patterns), but the natural_language_command tool significantly overlaps with list_orders, list_shipments, search_inventory, and others, creating ambiguity about when to use specific structured tools versus the flexible NL interface.

    Naming Consistency5/5

    Excellent consistency throughout. All tools use snake_case with clear verb_noun patterns (get_, list_, check_, search_, optimize_, compare_). Verb usage is predictable: 'get' for specific items, 'list' for collections, 'search' for filtered queries.

    Tool Count4/5

    Twenty tools is slightly above the ideal range but reasonable given the domain complexity spanning inventory, orders, shipments, fleet, warehouse, and AI analytics. Each tool serves a distinct supply chain function without obvious redundancy.

    Completeness4/5

    Strong coverage across the supply chain lifecycle: inventory management, order tracking, shipment logistics, fleet optimization, and financial metrics. Minor gaps in explicit write/update operations (create_order, update_inventory), though natural_language_command appears to handle some mutations.

    Maintenance

    ActivityInactive
    ResponsivenessSyncing