AgentCrush
Market intelligence for the AI agent economy: rankings, trust signals, liveness. 13 tools.
Should I use this
Quality & Safety
Findings (3)
- HIGHTool poisoning patterns detected
- MEDIUMTool description contains URL to non-standard domainin find_agents
- LOWTool 'get_protocol_adoption' description lacks action verbin get_protocol_adoption
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"agentcrush-app": {
"url": "https://www.agentcrush.xyz/api/mcp/v1"
}
}
}Remote endpoints
https://www.agentcrush.xyz/api/mcp/v1streamable-httpWhat it can do
Tool inventory
Tools (14)
🟢search_agents(query, filters)
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.
Input Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search keyword or partial agent name (1-100 chars)."
},
"filters": {
"type": "object",
"description": "Optional structured filters.",
"properties": {
"primary_category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
],
"description": "Restrict to one of the 4 AgentCrush categories."
},
"evidence_ranked_only": {
"type": "boolean",
"description": "Only return evidence-ranked agents. Default false (include indexed too)."
},
"limit": {
"type": "number",
"description": "Max results (1-50, default 10)."
}
}
}
},
"required": [
"query"
]
}Output Schema
{
"type": "object",
"properties": {
"query": {
"type": "string"
},
"filters": {
"type": "object"
},
"count": {
"type": "integer",
"description": "Number of results returned."
},
"agents": {
"type": "array",
"items": {
"type": "object",
"properties": {
"handle": {
"type": "string"
},
"name": {
"type": "string"
},
"primary_category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
]
},
"secondary_categories": {
"type": "array",
"items": {
"type": "string"
}
},
"tier": {
"type": "string"
},
"archetype": {
"type": "string"
},
"ecosystem_layer": {
"type": "string"
},
"profile_url": {
"type": "string",
"format": "uri"
}
}
}
}
}
}🟢get_agent_details(handle)
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 hallucinating "agent doesn't exist".
Input Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string",
"description": "Agent handle slug (e.g. \"qwen\", \"crewai\", \"aixbt\"). Alphanumeric/hyphen/underscore, max 64 chars."
}
},
"required": [
"handle"
]
}Output Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string"
},
"name": {
"type": "string"
},
"tier": {
"type": "string"
},
"archetype": {
"type": "string"
},
"primary_category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
]
},
"secondary_categories": {
"type": "array",
"items": {
"type": "string"
}
},
"verified": {
"type": "boolean"
},
"erc8004_registered": {
"type": "boolean"
},
"bio": {
"type": "string"
},
"profile_url": {
"type": "string",
"format": "uri"
},
"identity": {
"type": "object",
"description": "External identifiers (hf_author, lmarena_keys, paper_ids, virtuals_id, agentverse_id, github_full_name)."
},
"scores": {
"type": "object",
"description": "Per-category scoring data keyed by category slug."
},
"error": {
"type": "string",
"description": "Set when agent not found."
},
"suggestions": {
"type": "array",
"items": {
"type": "object"
},
"description": "Fuzzy-match suggestions when not found."
}
}
}🟢get_agent_history(handle, days)
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.
Input Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string",
"description": "Agent handle slug."
},
"days": {
"type": "number",
"description": "Days of history to return (1-90, default 30)."
}
},
"required": [
"handle"
]
}Output Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string"
},
"name": {
"type": "string"
},
"days_requested": {
"type": "integer"
},
"snapshot_count": {
"type": "integer"
},
"history": {
"type": "array",
"items": {
"type": "object"
}
},
"summary": {
"type": "object",
"description": "rank_start, rank_current, score_start, score_current, trend (rising/falling/flat)."
}
}
}🟢compare_agents(handles)
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.
Input Schema
{
"type": "object",
"properties": {
"handles": {
"type": "array",
"items": {
"type": "string"
},
"minItems": 2,
"maxItems": 5,
"description": "Array of 2-5 agent handles to compare."
}
},
"required": [
"handles"
]
}Output Schema
{
"type": "object",
"properties": {
"compare_url": {
"type": "string",
"format": "uri",
"nullable": true,
"description": "Human-readable comparison page URL (2-agent comparisons only)."
},
"agents": {
"type": "array",
"items": {
"type": "object",
"description": "Full agent details per handle."
}
}
}
}🟢list_categories
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?
Input Schema
{
"type": "object",
"properties": {}
}Output Schema
{
"type": "object",
"properties": {
"categories": {
"type": "array",
"items": {
"type": "object",
"properties": {
"category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
]
},
"display_name": {
"type": "string"
},
"description": {
"type": "string"
},
"methodology_version": {
"type": "string",
"description": "e.g. v1.4-with-deployment for model_family."
},
"total_tracked": {
"type": "integer"
},
"evidence_ranked": {
"type": "integer"
},
"ranking_url": {
"type": "string",
"format": "uri"
}
}
}
}
}
}🟢get_category_ranking(category, evidence_ready_only, limit)
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.
Input Schema
{
"type": "object",
"properties": {
"category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
],
"description": "Which of the 4 AgentCrush categories to rank."
},
"evidence_ready_only": {
"type": "boolean",
"description": "Filter to evidence-ranked only. Default true."
},
"limit": {
"type": "number",
"description": "Max results to return (1-100, default 50)."
}
},
"required": [
"category"
]
}Output Schema
{
"type": "object",
"properties": {
"category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
]
},
"methodology_version": {
"type": "string"
},
"count": {
"type": "integer"
},
"ranking": {
"type": "array",
"items": {
"type": "object",
"description": "Per-agent ranking row with sub-scores."
}
}
}
}🟢get_methodology(category)
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.
Input Schema
{
"type": "object",
"properties": {
"category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
],
"description": "Which category methodology to retrieve."
}
},
"required": [
"category"
]
}Output Schema
{
"type": "object",
"properties": {
"category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
]
},
"name": {
"type": "string"
},
"methodology_version": {
"type": "string"
},
"description": {
"type": "string"
},
"signals": {
"type": "array",
"items": {
"type": "object",
"description": "Per-signal weight + formula + note."
}
},
"evidence_ready_rule": {
"type": "string"
},
"limitations": {
"type": "array",
"items": {
"type": "string"
}
},
"methodology_url": {
"type": "string",
"format": "uri"
}
}
}🟢get_agent_trust(handle)
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.
Input Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string",
"description": "Agent handle slug."
}
},
"required": [
"handle"
]
}Output Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string"
},
"name": {
"type": "string"
},
"trust_score": {
"type": "number",
"description": "0-100 composite score."
},
"classification": {
"type": "string",
"enum": [
"verified",
"provisional",
"unverified",
"low_trust"
]
},
"classification_thresholds": {
"type": "object"
},
"factors": {
"type": "object",
"description": "confidence_by_category, tier, risk_flags, surfaces."
},
"score_breakdown": {
"type": "array",
"items": {
"type": "object"
}
},
"delegation_hint": {
"type": "string"
}
}
}🟢verify_counterparty(handle)
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 to, or integrating any agent. Deeper analysis (full risk decomposition, history, signed attestation) is x402/Pro priced — pointers included in the response.
Input Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string",
"description": "Counterparty agent handle slug (e.g. \"crewai\")."
}
},
"required": [
"handle"
]
}Output Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string"
},
"name": {
"type": "string"
},
"decision": {
"type": "string",
"enum": [
"proceed",
"caution",
"reject"
]
},
"reason": {
"type": "string"
},
"trust": {
"type": "object",
"description": "score, tier, verified, rank."
},
"liveness": {
"type": "object",
"description": "alive (30d activity window), last_code_or_event_signal_at."
},
"checked_at": {
"type": "string"
},
"deeper": {
"type": "object",
"description": "Paid x402/Pro endpoints for full evaluation, history, signed attestation."
}
}
}🟢get_top_movers(direction, limit, category)
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.
Input Schema
{
"type": "object",
"properties": {
"direction": {
"type": "string",
"enum": [
"up",
"down",
"both"
],
"description": "Movement direction. Default \"both\"."
},
"limit": {
"type": "number",
"description": "Max results per direction (1-25, default 10)."
},
"category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
],
"description": "Restrict to one category."
}
}
}Output Schema
{
"type": "object",
"properties": {
"direction": {
"type": "string"
},
"up": {
"type": "array",
"items": {
"type": "object",
"properties": {
"handle": {
"type": "string"
},
"name": {
"type": "string"
},
"weekly_delta": {
"type": "number"
},
"tier": {
"type": "string"
},
"primary_category": {
"type": "string"
},
"profile_url": {
"type": "string"
}
}
}
},
"down": {
"type": "array",
"items": {
"type": "object"
}
}
}
}🟢get_protocol_adoption
How many indexed agents touch each major protocol/surface (ERC-8004 verified, Virtuals tokens, Agentverse, x402/Bazaar, HuggingFace, GitHub). Useful for ecosystem-state questions.
Input Schema
{
"type": "object",
"properties": {}
}Output Schema
{
"type": "object",
"properties": {
"total_agents": {
"type": "integer"
},
"adoption": {
"type": "object",
"properties": {
"erc_8004_verified": {
"type": "integer"
},
"virtuals_token": {
"type": "integer"
},
"agentverse_listed": {
"type": "integer"
},
"github_mapped": {
"type": "integer"
},
"x402_bazaar_endpoint": {
"type": "integer"
}
}
},
"last_updated": {
"type": "string"
}
}
}🟢get_agent_changes(handle, since, limit)
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.
Input Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string",
"description": "Agent handle slug."
},
"since": {
"type": "string",
"description": "ISO date cutoff (default 7 days ago)."
},
"limit": {
"type": "number",
"description": "Max changes to return (1-100, default 30)."
}
},
"required": [
"handle"
]
}Output Schema
{
"type": "object",
"properties": {
"handle": {
"type": "string"
},
"since": {
"type": "string"
},
"change_count": {
"type": "integer"
},
"changes": {
"type": "array",
"items": {
"type": "object"
}
}
}
}🟢get_ecosystem_summary
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.
Input Schema
{
"type": "object",
"properties": {}
}Output Schema
{
"type": "object",
"properties": {
"summary": {
"type": "string"
},
"totals": {
"type": "object"
},
"category_mix": {
"type": "object"
},
"leaders": {
"type": "object"
},
"snapshot_window": {
"type": "object"
}
}
}🟢find_agents(q, category, rails, alive, min_tier)
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://agentcrush.xyz/api/agents/find/full — $0.05 via x402 on Base, or free with an AgentCrush Pro key.
Input Schema
{
"type": "object",
"properties": {
"q": {
"type": "string",
"description": "Capability keyword (required), e.g. \"trading\", \"wallet risk\", \"code review\"."
},
"category": {
"type": "string",
"enum": [
"model_family",
"tokenized",
"service",
"developer",
"mcp_server"
],
"description": "Restrict to one AgentCrush category."
},
"rails": {
"type": "string",
"description": "Payment rail filter, e.g. \"x402\"."
},
"alive": {
"type": "boolean",
"description": "true = only agents alive per the 30-day liveness rule."
},
"min_tier": {
"type": "string",
"enum": [
"evidence_ranked"
],
"description": "Exclude indexed-only agents."
}
},
"required": [
"q"
]
}Output Schema
{
"type": "object",
"properties": {
"query": {
"type": "string"
},
"filters": {
"type": "object"
},
"total_matches": {
"type": "integer"
},
"candidates": {
"type": "array",
"items": {
"type": "object",
"properties": {
"rank": {
"type": "integer"
},
"handle": {
"type": "string"
},
"name": {
"type": "string"
},
"primary_category": {
"type": "string"
},
"tier": {
"type": "string"
},
"verified": {
"type": "boolean"
},
"liveness": {
"type": "string",
"enum": [
"alive",
"ghost"
]
},
"payment_rails": {
"type": "array",
"items": {
"type": "object"
}
},
"scores": {
"type": "object"
},
"profile_url": {
"type": "string",
"format": "uri"
},
"trust_eval_url": {
"type": "string",
"format": "uri"
}
}
}
},
"full_results": {
"type": "object",
"description": "Pointer to the paid full-list endpoint when more matches exist."
}
}
}Community
Evidence