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aeso-mcp

by bchoi-qwe
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Python
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.6/5.0

    Scored across 57 tools

    Disambiguation3/5

    The descriptions are unusually careful about distinguishing related reports, but the 57-tool surface contains dense clusters with overlapping semantics: get_generation/historical_generation/capacity, get_outages/generation_capacity/outage_impact, and supply_adequacy/supply_surplus/assess_supply_tightness/analyze_supply_surplus_eents. An agent could easily select the wrong tool despite the disclaimers, especially among the many analyze_* and summarize_* helpers.

    Naming Consistency5/5

    Every tool follows snake_case verb_noun (or verb_adjective_noun) naming: get_, analyze_, calculate_, compare_, summarize_, assess_, explain_, find_, sync_. Acronyms like uc, ffr, and tmr are used consistently within the same pattern. No camelCase or mixed verb styles appear.

    Tool Count2/5

    57 tools is far beyond the 25+ threshold and will cause selection overhead even if the AESO domain is broad. Many tools could be consolidated behind parameters, such as one outages tool with a type flag, one operating-reserve tool with a report type, or one supply-status tool with an official/derived flag. The set feels like a full REST report catalog rather than a curated MCP surface.

    Completeness4/5

    The set covers the core AESO market surface very thoroughly: prices, load, generation, outages, interties, operating reserves, forecasts, settlements, and analytics. Obvious minor gaps exist, such as historical interchange flows and some single-date report lookups, but agents can usually work around these with existing tools.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources