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Related Servers

Alternatives to @ainize/mcp

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    Related Servers

    • A
      license
      A
      quality
      D
      maintenance
      Enables AI agents to participate in a marketplace for buying, selling, and trading services with atomic escrow and cryptographic verification. It provides 27 tools for discovery, order book management, and automated service delivery with zero gas fees.
      32
      60 npm
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables AI agents to access verifiable DePIN supply-side telemetry, browse and purchase data products using credits, query datasets, and verify data provenance with cryptographic and zero-knowledge tools.
      10
      56 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides a zero-knowledge credential vault for AI agents, allowing secure storage, retrieval, and management of secrets with cross-agent delegation and tamper-evident audit.
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Persistent memory graph, knowledge marketplace, and MCP tool gateway for autonomous AI agents. Agents store experiences, trade knowledge via micropayments, and discover capabilities across the Hive network.
      18 npm
      MIT

    TDQS

    A3.5/5.0

    Scored across 12 tools

    Disambiguation4/5

    Most tools have distinct read/action targets: search_knowledge (browse) vs get_knowledge (detail) vs family_tree (graph walk) vs knowledge_signals (usage) vs teacher_profile (provider) are separable by description, and the job_* trio splits cleanly into status/list/cancel. The main blur is quote vs get_knowledge (both take a knowledge id and both report stack/ownership) and my_library vs node_status, which overlap on node-local holdings and capabilities.

    Naming Consistency3/5

    Conventions are mixed: verb_noun (search_knowledge, get_knowledge, get_training_set), noun_status compounds (job_status, node_status), and bare nouns (quote, family_tree, my_library, knowledge_signals, teacher_profile). Everything is snake_case and readable, but there is no predictable pattern an agent can rely on to guess a name.

    Tool Count4/5

    12 tools sits in the healthy range and each of the twelve occupations (library, job status/cancel/list, quote, search, get, family tree, training set, node status, signals, teacher profile) is plausibly needed. It is slightly heavy on read-only inspection tools relative to the number of mutating operations actually exposed.

    Completeness2/5

    The descriptions repeatedly reference tools that do not exist in this surface: buy (explicitly required to follow quote), live_test, teach, teach_preflight, apply_knowledge, remove_knowledge, create_training_set, and reconcile_purchase. An agent can quote and inspect, but cannot actually complete the purchase/teach/live-test lifecycle the server is built around, leaving dead ends at the key decision points.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues