Realmint launched an MCP server enabling AI agents to research and trade 3,000+ tokenized RWAs with structured issuer data, risk scores, and pricing.
AI & Agents ·
Realmint launched an MCP server designed to structure information about tokenized real-world assets for use by AI agents. The platform covers 3,000+ tokenized assets and provides agents with issuer details, risk scores, live pricing, asset histories, and available trading routes to enable research and execution.
The system assigns each asset a risk score from 0 to 100 based on six factors including liquidity, backing, exit rights, and issuer controls. Scores of 75 or above are considered standard range; 55 to 74 signals elevated risk requiring closer review; below 55 is flagged as high risk and may halt agent action unless explicitly overridden. Scores update as underlying conditions change, and Realmint stores earlier asset versions so agents can track material updates over time. The platform separates read-only research access from authenticated execution—agents can analyze assets without fund-moving permissions initially, with deposit and trading capabilities available after separate wallet delegation.
Realmint describes its scoring methodology as experimental and subject to refinement. The broader challenge remains unclear: as tokenized assets proliferate onchain, whether structured data layers like this will sufficiently bridge the gap between availability and usability within autonomous financial systems remains to be demonstrated at scale.