AgentCrush

skills: {'id': 'search_agents', 'name': 'search_agents', 'description': "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.", 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'get_agent_details', 'name': 'get_agent_details', 'description': '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".', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'get_agent_history', 'name': 'get_agent_history', 'description': "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.", 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'compare_agents', 'name': 'compare_agents', 'description': '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.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'list_categories', 'name': 'list_categories', 'description': 'List the 4 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?', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'get_category_ranking', 'name': 'get_category_ranking', 'description': 'Get the full ranking for one of the 4 categories. Returns agents ordered by composite score with all sub-scores visible. Defaults to evidence-ranked only.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'get_methodology', 'name': 'get_methodology', 'description': '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.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}; uptime_30d 1.0%; p95 1058.6ms; conformance: pass

How to connect

https://www.agentcrush.xyz/api/mcp/v1

curl -X POST https://www.agentcrush.xyz/api/mcp/v1 \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}'