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Computer Vision Carbon Credit Generator MCP
x402
Computer Vision Carbon Credit Generator MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.925501/call, status unknown (last checked 2026-10-10).
Executes a computer vision query to generate or assess carbon credit predictions via a monetized MCP node
Price / call$0.925501
Success—
StatusUnknown
How this service works
The premier global index of 1,069 monetized MCP nodes across 205 specialized subdomains. Gasless USDC runtime settlements via x402 V2 Spec on Base L2. Save 95% token context.
Output
A JSON object containing a 'prediction' boolean indicating whether the input query corresponds to a carbon-credit-qualifying scenario as assessed by the computer vision model.
Example use cases
Forest Cover Carbon Credit Check
“I have a satellite image description of a reforested area in Kenya — 'secondary growth woodland, approximately 200 hectares, no recent deforestation detected' — can you run it through the carbon credit vision model and tell me if it qualifies?”
Agricultural Land Carbon Assessment
“Run a carbon credit prediction on this land description: 'regenerative farmland with cover crops and no-till practices across 120 acres in Iowa' — does it pass the carbon credit threshold?”
Urban Green Space Eligibility
“Does a city park described as 'mature urban tree canopy, 15 hectares, established over 20 years with no removals' qualify for carbon credit generation according to the computer vision model?”
Technical details
Endpoint
POSThttps://api.m2mcent.com/computer-vision-carbon-credit-generator-mcp-929/api/execute?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, pay-per-call boolean assessment of carbon credit eligibility based on a natural language or descriptive visual query, especially when integrating into automated environmental compliance or carbon accounting pipelines that require lightweight, tokenized micro-transactions.
Side effects
- Missing or empty query field returns a 400 validation error
- Ambiguous or non-visual query text may produce unreliable boolean predictions
- Payment failure via x402 protocol results in 402 response before execution
- Server-side model errors return 500 with no prediction value
- Overly short or generic queries may yield low-confidence false negatives
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| queryrequired | string |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| predictionrequired | boolean |
Tags
x402
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