{"type":"mcp-server-v1","name":"Autonolas Mech III","description":"The mech executes AI tasks requested on-chain and delivers the results to the requester.","version":"1.0.0","endpoint":"https://f1e4affa9243b465.agent.propel.autonolas.tech","capabilities":{"tools":{"listChanged":false}},"auth":{"methods":[{"type":"api_key","header":"X-API-Key"},{"type":"wallet_signature","scheme":"eip712","header":"X-Signature"}],"required":["api_key","wallet_signature"]},"metadata":{"network":"polygon","serviceId":"44","sourceToolMetadataCid":"f0170122080430f6e1e84228e78a7ae9f829626288f774ec7e512ffb31f7d6e763cc0f543","generatedAt":"2026-09-17T21:42:51.644Z","marketplaceAddress":"eip155:137:0x343F2B005cF6D70bA610CD9F1F1927049414B582","mechAddress":"eip155:137:0xe7f818513a48d74c99b8bde153bee0b70dbb300b"},"tools":[{"name":"superforcaster_full_search","description":"A sibling of superforcaster that fetches full search-result pages (top organic results) and extracts the main article text via readability + markdownify, feeding the cleaned page body into the forecasting prompt instead of relying on Serper snippets alone. The forecasting prompt and prediction architecture are unchanged from superforcaster.","inputSchema":{"type":"string","description":"The text to make a prediction on"},"outputSchema":{"type":"object","description":"A JSON object containing the prediction and confidence","properties":{"requestId":{"type":"integer","description":"Unique identifier for the request"},"result":{"type":"string","description":"Result information in JSON format as a string","example":"{\n  \"p_yes\": 0.6,\n  \"p_no\": 0.4,\n  \"confidence\": 0.8,\n  \"info_utility\": 0.6\n}"},"prompt":{"type":"string","description":"The prompt used to make the prediction."}},"required":["requestId","result","prompt"]}},{"name":"superforcaster_market_aware","description":"A tool for making binary predictions on prediction markets. It estimates the probability that a market question resolves Yes. Departing from superforcaster_full_search, it fetches full search-result pages (top organic results) and extracts the main article text via readability + markdownify, feeding the cleaned page body into the forecasting prompt instead of relying on Serper snippets alone, and returns its forecast via OpenAI Structured Outputs. It optionally accepts market context on the request and reports objective properties of the question alongside the forecast; it never advises a trade action.","inputSchema":{"type":"string","description":"The text to make a prediction on"},"outputSchema":{"type":"object","description":"A JSON object containing the prediction and confidence","properties":{"requestId":{"type":"integer","description":"Unique identifier for the request"},"result":{"type":"string","description":"Result information in JSON format as a string","example":"{\n  \"p_yes\": 0.6,\n  \"p_no\": 0.4,\n  \"confidence\": 0.8,\n  \"info_utility\": 0.6\n}"},"prompt":{"type":"string","description":"The prompt used to make the prediction."}},"required":["requestId","result","prompt"]}},{"name":"superforcaster_polymarket_v4","description":"A tool for making binary predictions on markets using the Serper API and LLMs. v4 adds a step-4 evidence-reliability screen (prediction-market- odds filter, forward-looking-intent discount, TYPE A/B temporal-evidence classification, criterion-specificity check) for systematic overconfident-YES on Polymarket; consolidates the abandoned v4/v5 work (#375) into one tool off v1.","inputSchema":{"type":"string","description":"The text to make a prediction on"},"outputSchema":{"type":"object","description":"A JSON object containing the prediction and confidence","properties":{"requestId":{"type":"integer","description":"Unique identifier for the request"},"result":{"type":"string","description":"Result information in JSON format as a string","example":"{\n  \"p_yes\": 0.6,\n  \"p_no\": 0.4,\n  \"confidence\": 0.8,\n  \"info_utility\": 0.6\n}"},"prompt":{"type":"string","description":"The prompt used to make the prediction."}},"required":["requestId","result","prompt"]}},{"name":"superforcaster_polymarket_v2","description":"A tool for making binary predictions on markets using the Serper API and LLMs. Extends v1 with an explicit resolution-criterion specificity check for narrow-scope criteria.","inputSchema":{"type":"string","description":"The text to make a prediction on"},"outputSchema":{"type":"object","description":"A JSON object containing the prediction and confidence","properties":{"requestId":{"type":"integer","description":"Unique identifier for the request"},"result":{"type":"string","description":"Result information in JSON format as a string","example":"{\n  \"p_yes\": 0.6,\n  \"p_no\": 0.4,\n  \"confidence\": 0.8,\n  \"info_utility\": 0.6\n}"},"prompt":{"type":"string","description":"The prompt used to make the prediction."}},"required":["requestId","result","prompt"]}},{"name":"superforcaster_polymarket_v1","description":"A tool for making binary predictions on markets using the Serper API and LLMs.","inputSchema":{"type":"string","description":"The text to make a prediction on"},"outputSchema":{"type":"object","description":"A JSON object containing the prediction and confidence","properties":{"requestId":{"type":"integer","description":"Unique identifier for the request"},"result":{"type":"string","description":"Result information in JSON format as a string","example":"{\n  \"p_yes\": 0.6,\n  \"p_no\": 0.4,\n  \"confidence\": 0.8,\n  \"info_utility\": 0.6\n}"},"prompt":{"type":"string","description":"The prompt used to make the prediction."}},"required":["requestId","result","prompt"]}},{"name":"superforcaster_full_search_olas_predict_r1_14b","description":"Prediction market forecasting tool. A sibling of superforcaster_full_search that keeps its full-page search evidence pipeline and forecasting prompt unchanged and swaps the forecaster for Olas-Predict-R1-14B, a fine-tuned DeepSeek-R1-Distill-Qwen-14B served from a self-hosted vLLM endpoint. Returns p_yes, p_no, confidence and info_utility for a binary prediction market question.","inputSchema":{"type":"string","description":"The text to make a prediction on"},"outputSchema":{"type":"object","description":"A JSON object containing the prediction and confidence","properties":{"requestId":{"type":"integer","description":"Unique identifier for the request"},"result":{"type":"string","description":"Result information in JSON format as a string","example":"{\n  \"p_yes\": 0.6,\n  \"p_no\": 0.4,\n  \"confidence\": 0.8,\n  \"info_utility\": 0.6\n}"},"prompt":{"type":"string","description":"The prompt used to make the prediction."}},"required":["requestId","result","prompt"]}}]}