78trust / 100

FutureSmart AI Demos

by aidemos.com in Search & web

MCP serverPassing, checked 2 h ago

Search evidence-backed AI-tool reviews, rankings, use cases, comparisons & toolkits (read-only).

https://mcp.aidemos.com/mcp
Tools
17
open to any client
Uptime
100%
last 30 days
Response time
412 ms
554 ms slowest 5%
Last check
Passed
2 h ago, next in 4 h

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How to connect

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "futuresmart-ai-demos": {
      "type": "http",
      "url": "https://mcp.aidemos.com/mcp"
    }
  }
}

17 tools

  • answer

    ANSWER a buyer question in ONE call: which tool is best at a specific capability, with proof. Returns the resolved verdict our testing team's evidence supports — a named winner FOR THE ASKED CRITERION, every tested tool ranked with a comparable score /5, the CONDITIONS each…

  • list_use_cases

    List published use-case pages (how-to guides): id, title, slug, url, persona, category, updated_at.

  • list_rankings

    List published ranking pages ("best X"): id, title, slug, url, use_case, persona, category, tools_count, winner, tested_as_of, updated_at.

  • list_tools

    List published AI tool pages: id, name, slug, url, domain, personas[], categories[].

  • list_compares

    List published head-to-head comparison pages: id, title, slug, url, tool_a, tool_b, personas[], shared_use_cases[], updated_at.

  • list_toolkits

    List published toolkit pages (curated bundles): id, title, slug, url, category.

  • list_personas

    List personas with published-page counts per type {use_cases, rankings, tools, compares, toolkits}. The slugs are valid input for get_persona.

  • list_categories

    List the category vocabulary in use with per-type counts and a source flag ("collection"|"derived"), sorted by total.

  • search

    Search the published catalogue across use cases, rankings, tools, comparisons, and toolkits. Returns ranked light refs [{ kind, id, title, slug, url, snippet, score, meta }] — then call get_tool / get_ranking / get_use_case for full detail. `mode`: keyword (substring), semantic…

  • tools_in_ranking

    Given a ranking id, return the ranking {id,title,slug} and its ranked tools [{id,name,slug,url,rank,badge}] (badge: Best/Usable/Needs work/Unstable/Failed).

  • rankings_for_tool

    Given a tool id, return the tool {id,name,slug} and every ranking it appears in [{id,title,slug,url,use_case,rank,badge}].

  • get_persona

    Given a persona slug (from list_personas), return everything tagged with it: persona, use_cases[], rankings[], compares[], toolkits[], tools[]. Mirrors a persona landing page.

  • get_tool

    Full tool detail as a JSON+Markdown envelope: identity, pricing, per-feature scores, fit, FAQ, relationships (JSON) + our_take / in-depth review (Markdown). Includes `proof`: real artifact URLs (input/output screenshots, recordings) from the runs that tested it, each with the…

  • get_ranking

    Full ranking detail as a JSON+Markdown envelope: ranked tools (rank/badge/scores), criteria, winner, breakdown (JSON) + verdicts / final take (Markdown). Every ranked tool carries `proof`: real artifact URLs from the exact evidence run this page is bound to, each with the…

  • get_use_case

    Full use-case detail as a JSON+Markdown envelope: step guide, pros/cons, FAQ, tools used (JSON) + the full narrative guide (Markdown, full_md). null if unknown. Pass `fields` to project to only the keys you need (token-efficient).

  • get_evidence

    Query the evidence graph: observation cells (tool × test-scenario × criterion) → verdict, score, the researcher's note, and the REAL artifacts (input/output screenshots) that prove it. The ground truth behind every ranking — filter any combination of tool(s), scenario (slug…

  • compare_tools

    Evidence-aligned comparison of two tools, honesty enforced structurally: head_to_head (cells from the SAME test input — provable same-input comparison), related_not_same_input (same dimension, different runs — flagged), and each tool's unique evidence. Built from real…

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We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.

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