MCP server

AgentCrush

io.github.kristof-sudo/agentcrush-app

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Website Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

14

Token cost

About 2,249 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http agentcrush-app https://www.agentcrush.xyz/api/mcp/v1

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.agentcrush-app]
url = "https://www.agentcrush.xyz/api/mcp/v1"

Gemini CLI

{"mcpServers":{"agentcrush-app":{"httpUrl":"https://www.agentcrush.xyz/api/mcp/v1"}}}

Cursor

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

VS Code

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

Antigravity

agy mcp add agentcrush-app https://www.agentcrush.xyz/api/mcp/v1

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"agentcrush-app","server_url":"https://www.agentcrush.xyz/api/mcp/v1","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"agentcrush-app","server_url":"https://www.agentcrush.xyz/api/mcp/v1"}

Tools

• compare_agents ~139 tokens
  Compare 2-5 AI agents side-by-side across all their categories. Returns full per-agent scoring data + comparison context. Use for "X vs Y" queries. AgentCrush does not declare a universal winner — comparison shows evidence differences.
• find_agents ~301 tokens
  Counterparty discovery: "which agents can do X and are safe to pay?" Returns the top 3 ranked candidates with liveness (30-day Ghost Index rule), trust tier, verified payment rails (x402/MCP/ERC-8004), scores, and endpoints, plus the total match count. The full ranked list (up to 50) is at https://a
• get_agent_changes ~152 tokens
  Pairwise delta scan over an agent's recent snapshots. Reports material changes in score, rank, github_stars, follower_count, identity_type, etc. Mirror of GET /api/agent/{handle}/changes.
• get_agent_details ~170 tokens
  Get full details for a specific AI agent including all category scores it qualifies for (model_family, tokenized, service, developer). Returns identity, raw signals, sub-scores, evidence-ready status. Returns fuzzy-match suggestions if the handle is not found — LLMs should use these instead of hallu
• get_agent_history ~138 tokens
  Get rank and score history for an AI agent over the past 1–90 days. Daily snapshots, deduplicated per calendar day. Returns trend summary (rising/falling/flat). Useful for showing how an agent's standing has evolved.
• get_agent_trust ~125 tokens
  Single-call composite trust score (0-100) + classification (verified / provisional / unverified / low_trust) for delegation decisions. Combines confidence_tier, evidence tier, ERC-8004 verified identity, and risk flags. Mirror of GET /api/agent/{handle}/trust.
• get_category_ranking ~179 tokens
  Get the full ranking for one of the 5 categories. Returns agents ordered by composite score with all sub-scores visible. Defaults to evidence-ranked only.
• get_ecosystem_summary ~93 tokens
  One-call ecosystem-level summary: counts (total, evidence-ranked, archived), category mix (model_family/tokenized/service/developer/mcp_server), category leaders, snapshot volume last 30 days. Mirror of GET /api/trends/summary.
• get_methodology ~157 tokens
  Get the scoring methodology for one category — weights, signal sources, formulas, evidence-ready rule, and known limitations. **Methodology travels with data**: call this when explaining HOW a ranking works so the LLM can give a methodology-accurate answer instead of guessing.
• get_protocol_adoption ~80 tokens
  How many indexed agents touch each major protocol/surface (ERC-8004 verified, Virtuals tokens, Agentverse, x402/Bazaar, HuggingFace, GitHub). Useful for ecosystem-state questions.
• get_top_movers ~172 tokens
  Returns the top weekly rank movers (up + down) computed from agents.weekly_delta. Useful for surfacing notable changes since last week. Default limit 10 per direction.
• list_categories ~88 tokens
  List the 5 AgentCrush agent categories with tracked + evidence-ranked counts and current methodology versions. Use this for market-level discovery — what kinds of agents does AgentCrush track and how many of each?
• search_agents ~264 tokens
  Search AI agents by name or keyword across AgentCrush's evidence-ranked index. Returns matching agents with category, tier, and rank info. Use the `filters` object for structured constraints; future versions will add filter keys without breaking the API.
• verify_counterparty ~191 tokens
  THE pre-transaction question in one free call: should my agent deal with this counterparty right now? Returns proceed / caution / reject with reasoning. Liveness-aware: an agent with no public activity signal in 30+ days never gets a clean proceed, even if well-ranked. Use before paying, delegating

Browse

• GitHub tools
• HuggingFace tools
• Calendars
• Payments
• GitHub and code hosting
• Calling other AI models

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