AgentCrush
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/v1with 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.jsonfor 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.
| Category | Methodology | Tracked | Evidence-Ranked |
|---|---|---|---|
| Model Families | v1.4-with-deployment | 7 | 7 |
| Tokenized Agents | v1.1-tokenized-tvl | 16 | 16 |
| Service Agents | v1.1-service-forks | 28 | 28 |
| Developer Agents | v2.c-public | 1,289 | 86 |
For AI agents using AgentCrush
Multiple integration paths for LLM clients and AI agents:
# MCP server (JSON-RPC 2.0, 7 tools)
POST https://www.agentcrush.xyz/api/mcp/v1
# Discovery manifest
GET 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 LLMs
GET https://www.agentcrush.xyz/api/agent/{handle}/llm-summary
GET https://www.agentcrush.xyz/api/agents/bulk?handles=a,b,c
GET https://www.agentcrush.xyz/api/agent-economy/llm-summary
GET https://www.agentcrush.xyz/api/methodology/{category}/llm-summary
GET https://www.agentcrush.xyz/api/rankings/{category}/llm-summary
GET 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:
{
"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
npm install -g smithery
smithery mcp add kristof/agentcrush
Public docs
- Methodology hub — weights, formulas, evidence-ready rules per category
- Findings: methodology v1 launch — multi-signal inversion, Hermes case, anti-honeypot
- MCP server docs — Claude Desktop config, curl recipes, tool schemas
- Agent economy explainer
- AI agent frameworks
- A2A commerce
- x402 for agents
- MCP for agents
Labs
AgentCrush Labs offers Agent Commerce Readiness audits — same methodology applied in depth to evaluate specific agents/protocols.
- $299 startup audit
- $1,000+ implementation roadmap
- Case studies: aixbt + Coral + Daydreams (2026-05-13), CrewAI first cross-protocol agent (2026-05-08)
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
- Submission: /submit
- Email: contact@agentcrush.xyz
License
See /terms.
サーバー設定
{
"mcpServers": {
"agentcrush": {
"url": "https://www.agentcrush.xyz/api/mcp/v1"
}
}
}