MCP server

Doomscore Doom Official

vc.doomscore/doom

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Obsolescence-risk screening: predicts if a product gets absorbed into core LLM-platform features.

Website Source

At a glance

Type

MCP server

Publisher

doomscore.vc (verified by the MCP Registry)

Status

Working at last check

Tools

11

Token cost

About 1,400 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http doom https://mcp.doomscore.vc

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.doom]
url = "https://mcp.doomscore.vc"

Gemini CLI

{"mcpServers":{"doom":{"httpUrl":"https://mcp.doomscore.vc"}}}

Cursor

{"mcpServers":{"doom":{"url":"https://mcp.doomscore.vc"}}}

VS Code

{"servers":{"doom":{"type":"http","url":"https://mcp.doomscore.vc"}}}

Antigravity

agy mcp add doom https://mcp.doomscore.vc

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"doom","server_url":"https://mcp.doomscore.vc","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"doom","server_url":"https://mcp.doomscore.vc"}

Tools

• assess_product ~209 tokens
  Assess one product's obsolescence risk. Provide exactly ONE of description/url/pitch_company_id/deck_text. Async — returns job_id; poll get_assessment. Defaults to deep mode. Optionally pass requested_by to identify the caller (shown in the activity feed).
• doom_prep ~75 tokens
  Prep Gate. Validates config + confirms the roadmap-signals KB is within the staleness threshold. Fails closed if stale. Call before assess_product.
• get_assessment ~82 tokens
  Poll an assessment job_id. Returns status + the typed assessment when complete. Hard timeout — never hangs on pending.
• list_assessments ~66 tokens
  Recent assessments, filterable by verdict.
• list_kb_signals ~86 tokens
  List the active (signed, grounding) roadmap signals with their ids — use to find a signal_id to retire. Operator-only.
• list_signal_candidates ~145 tokens
  KB-refresh review queue. List auto-scraped candidate roadmap signals (default: pending). Operator-only. Approve/reject with review_signal_candidate; the weekly cron signs approved ones into the live KB.
• overview ~64 tokens
  Inspectable State. No input. Counts, recent activity, roadmap-signal freshness, health, last calibration run.
• record_outcome ~234 tokens
  Outcome-feedback (learning loop). Record what ACTUALLY happened to a previously-assessed product as a labeled calibration case; the weekly recalibration folds it into the gate. Operator-only (requires operator_key). Provide either job_id (links the case to that assessment + reuses its product) or pr
• retire_signal ~147 tokens
  UNLEARN a KB signal that became false/obsolete (e.g. a rumored feature cancelled, or a signal no longer predictive). Soft-deletes it (active=false) so it stops grounding assessments immediately — recoverable. Operator-only. Find the id via list_kb_signals.
• review_signal_candidate ~152 tokens
  Approve or reject a KB-refresh candidate signal. Operator-only. Approved candidates are signed (Ed25519) into the live roadmap_signals KB by the next refresh run; rejected ones are dropped. Controls what becomes grounding truth.
• supersede_calibration_case ~140 tokens
  UNLEARN a calibration case whose label turned out wrong or obsolete — retires it (active=false) so the recalibration gate stops scoring it. To correct, retire the wrong case then record_outcome the right one. Operator-only.

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