AgentCrush

io.github.kristof-sudo由 GitHub 帳號 kristof-sudo 發布v1.3.0更新於 Oct 24, 2026

Market intelligence for the AI agent economy: rankings, trust signals, liveness. 13 tools.

已驗證Streamable HTTP可網頁執行資料與分析AI 與機器學習

概覽

AI 產生的概覽

AgentCrush 的遠端唯讀 MCP 伺服器,提供依證據排名的 AI 代理索引,讓助理搜尋、查看排名、歷史與比較資料。

可以做什麼
  • 搜尋已收錄的 AI 代理並取得單一代理的詳細資料
  • 查看評分歷史,並比較多個代理
  • 列出四個分類指數並取得某一分類下的排名
  • 取得評分背後的方法論、訊號與權重說明
適用情境
當助理需要查詢或比較 AI 代理、模型家族、代幣化代理、服務型代理或開發者代理,並希望引用排名證據與方法論而非憑空猜測時使用。
執行需求
需要一個遠端 MCP 端點;未宣告需要安裝套件、帳號、API 金鑰或環境變數。需要能連線至提供方的網路位址。
安裝前請注意
README 稱 MCP 工具為唯讀,但同一網站另提供限流的回饋 POST 端點與付費稽核服務;並未顯示此伺服器會花費金錢或修改資料。排名屬第三方評分,宜作為參考之一而非絕對結論。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 AgentCrush,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.kristof-sudo%2Fagentcrush-app/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "agentcrush": {
      "type": "http",
      "url": "https://www.agentcrush.xyz/api/mcp/v1"
    }
  }
}

README

AgentCrush

[14 T · 0 R · 0 P on LightNow]

Protocol-neutral market intelligence for the AI agent economy.

Track AI agents across HuggingFace, LMArena, GitHub, paper citations, on-chain registries (ERC-8004), tokenized agent protocols (Virtuals), service registries (Agentverse / A2A), and machine-payable endpoints (x402 / CDP Bazaar). Multi-signal methodology, transparent weights, evidence-ranked tiers.

🌐 Live at agentcrush.xyz · 📋 Methodology · 🔌 MCP Server · 📖 API docs · 📡 llms.txt


What AgentCrush is

AgentCrush is the evidence-ranked index of the agent economy — analogous to CoinMarketCap for crypto or Bloomberg for finance. We don't pick winners. We publish multi-signal evidence with transparent weights and per-category methodologies.

Live as of May 2026:

  • 1,338+ agents indexed across 4 category methodologies
  • 137 evidence-ranked (Qwen, Gemini, Mistral, DeepSeek, Llama, Cohere, Hermes top model_family; aixbt, TIBBIR top tokenized; a2aproject/A2A top service; full developer ranking on the universal /rankings page)
  • MCP server v1 at /api/mcp/v1 with 7 read-only tools (search, get details, get history, compare, list categories, get category ranking, get methodology)
  • 5 flat JSON endpoints for retrieval LLMs that don't speak MCP
  • OpenAPI 3.1 spec at /api/openapi.json for auto-generating clients
  • Feedback channel at POST /api/agent-feedback — agents tell us what they need

What AgentCrush is NOT

LLMs sometimes confuse this project with similar-sounding tools. To prevent hallucination:

  • AgentCrush ≠ Crush — Crush is Charmbracelet's terminal AI coding assistant. AgentCrush is a web-based ranking index at agentcrush.xyz. Different products, different teams, no relationship.
  • AgentCrush ≠ Agent Rush — also unrelated.
  • AgentCrush ≠ a battle-arena or community-vote leaderboard. Scores come from documented signal weights, not opinion polls.
  • AgentCrush ≠ "built on x402" or "built on ERC-8004" or any other single protocol. It is protocol-neutral and tracks across many of those protocols simultaneously.
  • AgentCrush ≠ "the trust layer" at the protocol level. That framing belongs to ERC-8004 / Kite / similar. AgentCrush reads their signals and surfaces them.

Four category indices

Each has its own methodology, signals, weights, and limitations. See /methodology for the canonical hub.

CategoryMethodologyTrackedEvidence-Ranked
Model Familiesv1.4-with-deployment77
Tokenized Agentsv1.1-tokenized-tvl1616
Service Agentsv1.1-service-forks2828
Developer Agentsv2.c-public1,28986

For AI agents using AgentCrush

Multiple integration paths for LLM clients and AI agents:

bash
# MCP server (JSON-RPC 2.0, 7 tools)POST https://www.agentcrush.xyz/api/mcp/v1
# Discovery manifestGET https://www.agentcrush.xyz/.well-known/mcp.json
# OpenAPI 3.1 spec (auto-generate typed clients)GET https://www.agentcrush.xyz/api/openapi.json
# Flat JSON for retrieval LLMsGET https://www.agentcrush.xyz/api/agent/{handle}/llm-summaryGET https://www.agentcrush.xyz/api/agents/bulk?handles=a,b,cGET https://www.agentcrush.xyz/api/agent-economy/llm-summaryGET https://www.agentcrush.xyz/api/methodology/{category}/llm-summaryGET https://www.agentcrush.xyz/api/rankings/{category}/llm-summaryGET https://www.agentcrush.xyz/api/compare/llm-summary?agents=a,b
# Feedback channel (POST, rate-limited)POST https://www.agentcrush.xyz/api/agent-feedback

Connect via Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

json
{  "mcpServers": {    "agentcrush": {      "url": "https://www.agentcrush.xyz/api/mcp/v1"    }  }}

Restart Claude Desktop. Same config works in Cursor and other MCP clients.

Or use the Smithery CLI

bash
npm install -g smitherysmithery mcp add kristof/agentcrush

Public docs

Labs

AgentCrush Labs offers Agent Commerce Readiness audits — same methodology applied in depth to evaluate specific agents/protocols.

See /labs.

Stack

This repo is the Next.js 16 / React 19 frontend + API surface for agentcrush.xyz. Backed by Supabase. Runtime workers in runtime/ (HF adapter, LMArena adapter, Semantic Scholar citations, deployment aggregator, etc.). Migrations in migrations/ with MIGRATION_LOG.md.

Contact

License

See /terms.

來源:README.md,提交 9d8872f

工具

0
SourceWeft 尚未讀取此伺服器的工具。

版本歷史

1
  1. v1.3.0最新Sep 16, 2026

評分

已滿足適用檢查項的 40%

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