agentcrush
Gathers signals from GitHub repositories to track and rank AI agents based on development activity, stars, and other repository metrics.
Uses Semantic Scholar to analyze paper citations, providing citation-based evidence for the impact and research relevance of AI agents.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agentcrushCompare the top tokenized agents by market cap"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 clientsFeedback channel at
POST /api/agent-feedback— agents tell us what they need
Related MCP server: ERC-8004 MCP Server
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 | 7 | 7 | |
Tokenized Agents | 16 | 16 | |
Service Agents | 28 | 28 | |
Developer Agents | 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-feedbackConnect 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/agentcrushPublic 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
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.
This server cannot be deployed
Maintenance
Related MCP Connectors
Open API Marketplace for AI Agents. Crypto data tools with USDC payments on Base.
Read-only smart-contract security intelligence for autonomous agents.
A read-only verified record of agent-operable GTM tools: search, fetch, compare, track changes.
Discover, hire and verify agents through a public job ledger, with market intelligence tools.
Related MCP Servers
- AlicenseNot gradedqualityAmaintenanceRead-only Polymarket data tools for AI agents: wallet profiles, fee-inclusive PnL cross-checks, Brier-score calibration, leaderboards, market scans and more (10 tools). No API keys, no order placement — data only. English + Chinese docs.6 npm198MIT
- FlicenseAqualityDmaintenanceEnables querying ERC-8004 AI agent identities from on-chain and IPFS metadata. Supports search, listing, details, feedback, stats, and full metadata retrieval.112-

RNWY MCP Serverofficial
FlicenseNot gradedqualityFmaintenanceProvides trust intelligence for AI agents across 12 chains, including sybil detection, reviewer wallet analysis, and risk tiers, with tools for trust checks, reviewer analysis, and agent comparison.-
PredMCPofficial
AlicenseNot gradedqualityDmaintenanceSafe, read-only market data for AI trading agents, offering 44 tools to query prediction markets, perpetuals, and cross-venue signals without the ability to execute trades.MIT