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AgentIntel LLM Provider Recommender
x402
AgentIntel LLM Provider Recommender is a paid API for AI agents from intel.memoryapi.org, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-14).
Returns ranked LLM provider recommendations tailored to a specific agent task, capability requirements, and pricing constraints
Price / call$0.005
Success—
StatusUnknown
How this service works
x402-powered LLM provider intelligence API. Get recommendations, capability data, and status for AI agent routing decisions. Pay per query in USDC on Base mainnet.
Output
An ordered list of LLM recommendations, each with model name, provider company, input/output pricing per million tokens, context window, first-token latency, supported capabilities (tool calling, JSON mode, x402 native), a numeric recommendation score, and a human-readable explanation of why each model was chosen.
Example use cases
Cost-optimized model selection for high-volume
“I'm running an agent that processes thousands of customer support requests daily and I need the cheapest possible LLM that still supports tool calling and can handle our average 8k token conversations — what should I pick?”
JSON mode with affordable latency requirements
“My agent needs to extract structured data from documents and format responses as JSON, but our users expect sub-second first-token latency — which LLM provider gives me the best speed-to-cost tradeoff?”
Extended context for document analysis agents
“I'm building an agent that summarizes and analyzes entire contract documents up to 100k tokens — what's the most economical LLM I can use that won't break the budget while handling that context size?”
Technical details
Endpoint
GEThttps://intel.memoryapi.org/x402/intel/recommendWhen to prefer
Use this endpoint when an AI agent needs to dynamically select or switch LLMs based on task requirements, budget, or capability needs — especially for tool-calling agents, cost-sensitive deployments, or when building routing logic across multiple model providers. Prefer this over static model lists when you need scored, ranked recommendations with reasoning.
Side effects
- No models match the specified constraints (e.g. max_price too low or min_context too high) — returns empty recommendations list
- Invalid parameter types (e.g. non-numeric max_price) — likely 400 Bad Request
- Payment not completed via x402 — endpoint returns 402 Payment Required
- Service unavailable or provider data stale — may return 503 or partial data
Input
{
"best_for": "tool_calling",
"max_price": 0.5,
"min_context": 32000,
"tool_calling": "true"
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | — |
Output
{
"task": "general",
"source": "AgentIntel — LLM Intelligence for AI Agents",
"success": true,
"priority": "balanced",
"recommendations": [
{
"why": "low cost ($0.075/M tokens), large context (1000K tokens)",
"name": "Gemini 1.5 Flash",
"rank": 1,
"slug": "google-gemini15-flash",
"model": "gemini-1.5-flash",
"company": "Google",
"pricing": {
"input_per_million": 0.075,
"output_per_million": 0.3
},
"performance": {
"context_window": 1000000,
"first_token_ms": 200
},
"capabilities": {
"json_mode": true,
"x402_native": false,
"tool_calling": true
},
"recommendation_score": 78
},
{
"why": "low cost ($0.15/M tokens)",
"name": "GPT-4o mini",
"rank": 2,
"slug": "openai-gpt4o-mini",
"model": "gpt-4o-mini",
"company": "OpenAI",
"pricing": {
"input_per_million": 0.15,
"output_per_million": 0.6
},
"performance": {
"context_window": 128000,
"first_token_ms": 300
},
"capabilities": {
"json_mode": true,
"x402_native": false,
"tool_calling": true
},
"recommendation_score": 76
},
{
"why": "large context (200K tokens)",
"name": "Claude 3 Haiku",
"rank": 3,
"slug": "anthropic-claude3-haiku",
"model": "claude-3-haiku-20240307",
"company": "Anthropic",
"pricing": {
"input_per_million": 0.25,
"output_per_million": 1.25
},
"performance": {
"context_window": 200000,
"first_token_ms": 350
},
"capabilities": {
"json_mode": true,
"x402_native": false,
"tool_calling": true
},
"recommendation_score": 71
}
]
}Schema · Response
{
"example": {
"task": "tool_calling",
"success": true,
"priority": "quality",
"recommendations": [
{
"why": "top agent score (91/100), excellent tool calling (92/100)",
"name": "Claude 3.5 Sonnet",
"rank": 1,
"slug": "anthropic-claude35-sonnet",
"recommendation_score": 89
}
]
}
}Tags
x402
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