A
licenseC
qualityD
maintenanceExposes a bio-hybrid neuromorphic simulation pipeline (SNN, consciousness proxies, wetware integration) as MCP tools, resources, and prompts for AI assistants.
50
MIT
ASTRA MCP Server
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TDQS
C2.3/5.0
Scored across 49 tools
Disambiguation4/5
Tools are grouped by domain (tcai, wm, sensor, snn, np) and each description specifies a distinct subsystem or function. Some overlap exists among reporting tools (e.g., tcai_metrics, tcai_second_order, tcai_metaconsciousness), but their detailed descriptions clarify differences. Overall, an agent can usually select the right tool with careful reading.
Naming Consistency2/5
Naming conventions are inconsistent. Some tools use verb-first patterns (get_system_status, set_parameter, export_snapshot), others use domain-prefix + noun (np_status, sensor_status, tcai_self_model), and still others use domain-prefix + verb (wm_encode, tcai_reset, sensor_fuse). While the domain prefixes help organize tools, the lack of a uniform verb_noun pattern makes the set feel chaotic.
Tool Count2/5
With 49 tools, the server feels overloaded. The broad scope (SNN simulation, world model, sensors, consciousness metrics, organoid control) justifies a larger toolkit, but the sheer number likely overwhelms agents and increases selection errors. A more streamlined set or grouped sub-servers would be more appropriate.
Completeness4/5
The tool surface covers the major subsystems comprehensively: sensor encoding and fusion, world model training/prediction/planning, SNN stepping and reset, consciousness cycle and metacognition, memory storage/retrieval, and neuroplatform stimulation/queries. Minor gaps exist (e.g., no explicit raw SNN waveform export, no tool to delete memories), but agents can accomplish core workflows.
Maintenance
ActivityInactive
ResponsivenessNo issues