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Alternatives to ultratribe-mcp

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    Related Servers

    • 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
      3
      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables compatible agents to call registered local tools and read resources through one stdio server, including harness preparation, knowledge search and document management, memory retention/recall, correction proposals, advisory decisions, tool/skill discovery, and log/source inspection.
      2
      Apache 2.0
    • A
      license
      B
      quality
      A
      maintenance
      Exposes a local-first personal brain to any MCP client, letting agents perform identity-grounded memory recall, simulate stances and value conflicts, propose or approve audited guardrail changes, take snapshots with drift comparison, and run a neural validation harness. Everything runs against a local SQLite neuron/synapse memory graph with consent-gated, append-only auditing.
      6
      CC BY-4.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI models to access external services including weather data, file system operations, and SQLite database interactions through a standardized JSON-RPC interface. Features production-ready architecture with security, rate limiting, and comprehensive error handling.
      221 npm
      MIT

    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

    ActivityMaintained
    ResponsivenessNo issues