Qveris: Connect AI agents to 10,000+ real-world tools and APIs

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Autonomous AI agents in computational finance often encounter severe data integration bottlenecks. Upstream financial endpoints remain highly fragmented, gated behind disparate subscription tiers, subject to rigid rate limitations, and structured around non-standard schemas that destabilize execution loops. QVeris (https://qveris.ai/) provides a unified infrastructure platform designed to bridge autonomous software agents directly with real-world financial endpoints. The platform connects developers to over 10,000 live capabilities across quantitative pricing, macroeconomic indicators, SEC regulatory filings, equity fundamentals, crypto liquidity, and alternative sentiment data. Operational Architecture: 1. Dynamic Discovery: Agents search for required endpoints at runtime using plain natural language rather than relying on bloated prompt contexts. 2. Parameter Inspection: The platform provides pre-call introspection of schemas, latency profiles, and cost metrics to prevent payload errors and hallucinations. 3. Standardized Execution: Endpoints execute through unified JSON schemas across REST, Python and JavaScript SDKs, and the Model Context Protocol (MCP). Repository and Developer Documentation: - Platform URL: https://qveris.ai/ - Open-Source Agent Toolkit: https://github.com/QVerisAI/qveris-agent-toolkit