neurograph
Related Servers
Alternatives to neurograph
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityBmaintenanceEnables AI clients to access virome datasets and external bioinformatics APIs through MCP tools, including Wikipedia, PubMed, NCBI Taxonomy, read-only SQL over S3 Parquet, pandas/Plotly analyses, and map visualizations, while keeping the client decoupled from data and business logic.-
- AlicenseNot gradedqualityBmaintenanceExposes a shared graph-based context engine as MCP tools for Claude, Copilot, and other AI agents, enabling knowledge ingestion, recall, search, and LLM-ready context assembly across sessions.1Apache 2.0
- FlicenseNot gradedqualityDmaintenanceEnables AI tools to access and contribute to shared semantic memory, supporting search, capture, and curation of knowledge across multiple brains via the MCP protocol.-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to procedurally generate, transform, inspect, and export 3D meshes and scenes through MCP tools.MIT
- FlicenseBqualityBmaintenanceEnables AI agents to query an air-gapped enterprise knowledge vault via seven MCP tools for deterministic and hybrid retrieval, entity graph traversal, context compression, archive inspection, onboarding scans, and node status.7-
- AlicenseCqualityDmaintenanceExposes a bio-hybrid neuromorphic simulation pipeline (SNN, consciousness proxies, wetware integration) as MCP tools, resources, and prompts for AI assistants.50MIT
TDQS
Scored across 12 tools
Most tools have clearly distinct purposes, but a few close pairs exist: render_brain vs render_network both visualize atlas connectivity, and calculate_laplacian vs calculate_spectrum both operate on graph spectra. The descriptions clarify the different output modalities well enough to avoid serious misselection.
All tool names follow a consistent verb_noun snake_case pattern: search_region, get_connectivity, render_network, find_homologues, propose_dataset_ingestion. There are no mixed conventions or vague generic verbs.
Twelve tools is well within the ideal range and each tool covers a distinct aspect of the domain: exploration, connectivity, spectral analysis, visualization, species comparison, and dataset ingestion. The count feels appropriately scoped for a specialized neuroimaging server.
The toolset covers the core workflows well: searching regions and tracts, computing connectivity and paths, spectral analysis, rendering visualizations, comparing species, and proposing dataset ingestion. Minor gaps exist, such as no direct list_atlases or list_species tool, but these can be worked around via search_region and find_homologues.