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Alternatives to ultratribe-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
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      quality
      C
      maintenance
      Enables AI clients to perform sandboxed file-system operations, read-only SQLite querying and schema inspection, environment diagnostics, and cryptographic hashing over Stdio or HTTP using JSON-RPC.
      2
      MIT
    • A
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables deterministic evaluation of saccadic peak velocity saturation, reaction latency, antisaccade directional error rate, and frontal executive inhibitory control through JSON-RPC tool integration for LLMs and autonomous agents.
      MIT
    • F
      license
      A
      quality
      B
      maintenance
      Exposes NeuroGraph's scientific API to AI models as MCP tools, enabling them to query, analyze, and visualize brain networks — regions, tracts, connectivity, literature, and cross-species homologies — drawn from a portable SSD-based neuroimaging data library. Lets models read real atlas data, load datasets, compute graph metrics, and produce visualization scene descriptors without acting as the scientific engine itself.
      12
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      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP-compatible clients to manage and run local or cloud LLMs, generate completions and embeddings, and perform web search/fetch through exposed tools.
      956 npm
      AGPL 3.0

    TDQS

    B3.3/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: system diagnostics, inference benchmarking, listing supported datasets, and fetching atlas regions. There is no meaningful overlap between any two tools.

    Naming Consistency4/5

    Three tools follow a clear verb_noun pattern (benchmark_inference, list_supported_studies, get_atlas_regions), but system_diagnostics breaks the pattern by using a noun phrase. The naming remains readable and mostly consistent.

    Tool Count4/5

    Four tools is a reasonable size for a specialized server, but the set feels slightly minimal for the breadth of 'neural decoding' hinted at by the study and atlas tools. Still, each tool has a clear role and the count is not problematic.

    Completeness3/5

    The tools cover diagnostics, benchmarking, study listing, and atlas region lookup, but there are no tools to fetch study details, access actual neural data, or run decoding workflows. This creates notable gaps if the server is meant to support end-to-end neural decoding research.

    Maintenance

    ActivitySlowing
    ResponsivenessNo recent community issues