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Agentcrush App MCP Server

by Kristof Sudo
Developer ToolsUse Caution3.5MCP RegistryLocalRemote
Free

Server data from the Official MCP Registry

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

About

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

Remote endpoints: streamable-http: https://www.agentcrush.xyz/api/mcp/v1

Security Report

3.5
Use Caution3.5High Risk

AgentCrush is a protocol-neutral agent economy index with an MCP server that provides read-only access to ranking and metadata. The codebase demonstrates reasonable security practices for a data aggregation service, with proper use of environment variables for credentials and no obvious malicious patterns. However, there are moderate concerns around error handling in data ingestion workers, potential information disclosure through verbose logging, and some areas where input validation could be more rigorous. Permissions align well with the service's purpose of aggregating data from multiple external sources. Supply chain analysis found 7 known vulnerabilities in dependencies (0 critical, 1 high severity).

4 files analyzed ยท 15 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

env_vars

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

database

Check that this permission is expected for this type of plugin.

How to Install & Connect

Available as Local & Remote

This plugin can run on your machine or connect to a hosted endpoint. during install.

Documentation

View on GitHub

From the project's GitHub README.

AgentCrush

smithery badge

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.

๐ŸŒ Live at agentcrush.xyz ยท ๐Ÿ“‹ Methodology ยท ๐Ÿ”Œ MCP Server ยท ๐Ÿ“– API docs ยท ๐Ÿ“ก llms.txt


What AgentCrush is

AgentCrush is the evidence-ranked index of the agent economy โ€” 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 โ€” agents tell us what they need

What AgentCrush is NOT

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

  • AgentCrush โ‰  Crush โ€” 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 โ‰  Agent Rush โ€” also unrelated.
  • AgentCrush โ‰  a battle-arena or community-vote leaderboard. Scores come from documented signal weights, not opinion polls.
  • AgentCrush โ‰  "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 โ‰  "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:

# 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 โ€” weights, formulas, evidence-ready rules per category
  • Findings: methodology v1 launch โ€” multi-signal inversion, Hermes case, anti-honeypot
  • MCP server docs โ€” 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 โ€” 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.

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Links

Source CodeDocumentationRemote Endpoint

Details

Published May 17, 2026
Version 1.3.0
0 installs
Local & Remote Plugin

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