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CTM VoiceAI MCP

CTM VoiceAI MCP

by CTMJSON
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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

    A3.5/5.0

    Scored across 11 tools

    Disambiguation4/5

    The read/fetch tools (get_calls, get_voice_bots, list_runs, run_status, write_report) each map to a distinct step of the review flow, and step numbering in descriptions helps. The weak spot is the six auth tools: ctm_voiceai_configured vs ctm_voiceai_auth_status both report storage/state, and auth_login (device flow) vs auth_url+auth_exchange (web flow) are two paths to the same goal, which invites misselection.

    Naming Consistency3/5

    All names share the ctm_voiceai_ prefix and snake_case, but the internal ordering mixes conventions: verb-first (list_runs, get_calls, write_report) alongside resource-first (auth_status, auth_exchange, auth_url, run_status). ctm_voiceai_configured breaks the pattern further by using a past-tense adjective with no verb.

    Tool Count4/5

    11 tools is a sensible size for an OAuth plus review-and-report workflow, and each tool does earn a slot. It is slightly top-heavy, though, with 6 of 11 tools devoted to authentication while the actual analysis flow gets 5.

    Completeness4/5

    The surface covers the full auth lifecycle (url/exchange/login/logout/status/configured) plus run listing, run status, agent and call retrieval, and report writing, so an agent can complete the review loop end to end. Minor gaps: no explicit run-start trigger or date-range filtering on get_calls, but these are workable around via the batch plan.

    Maintenance

    ActivitySlowing
    ResponsivenessNo recent community issues

    Resources