OpenRouter
Model routing for compatibility and fallback checks.用于兼容性与故障回退检查的模型路由。
Official documentation官方文档OpenRouter provider detailsOpenRouter 服务商详情
Discover, inspect, and test external capabilities through QVeris, with explicit inputs, permissions, costs, and traceable outputs.发现并检查 QVeris 外部能力,核对输入、权限与费用,再用可追溯输出验证调用。
Published: March 16, 2026 · By the QVeris Team发布日期:2026年3月16日 · 由 QVeris 团队制作

Infrastructure designed from day one to connect agents with verified real-world capabilities.
Modern AI agents need to call external tools to do real work — market data, KYC checks, document parsing, weather APIs, and thousands more. But each tool comes with its own API, auth method, rate limits, error handling, and billing. Integrating a handful is manageable. Integrating dozens is a maintenance tax that slows teams down.
QVeris solves this with a discover-first architecture. Your agent describes the capability it needs in natural language, and QVeris finds the best match from 10,000+ verified tools across multiple verified providers. One protocol. One API key. Reduce per-provider integration work.
It is not an LLM. It is not an agent framework. It is the routing layer that connects agents to the real world — discover, inspect, and call, all in one unified flow.
Three steps. Discovery and inspection are always free. You only spend credits when your agent makes a call.
Your agent submits a natural-language query — "today's S&P 500 movers," "KYC check on this entity," or "extract tables from this PDF." QVeris searches across 10,000+ capabilities and returns a ranked list of matches, each tagged with estimated cost, average execution time, historical success rate, and provider name. No hardcoded endpoints. No pre-registration.
Before committing, your agent inspects any candidate capability to see its full parameter schema, usage examples, billing rules, and live quality metrics. Compare multiple capabilities side by side and choose the best one for the task. Zero-cost, zero-risk.
Your agent calls the selected capability with structured parameters. QVeris executes in a sandboxed environment and returns structured JSON — result payload, unique execution ID, billing details, and remaining credit balance. Every call is traced from agent to execution.
From finance-related capabilities to general developer tools, sourced from a growing provider network.
Real-time and historical market data across equities, FX, commodities, and indices. Built for quantitative workflows and trading agents.
Earnings data, analyst consensus, valuation models, and fundamentals. Give your research agent a complete data foundation.
KYC verification, sanctions screening, and regulatory data. Built for fintech agents needing compliance-aware capabilities.
Blockchain data, DeFi metrics, stablecoin flows, and wallet intelligence. Supports crypto and traditional market workflows.
News sentiment, social media analytics, event-driven indicators, and macroeconomic surprise data. Go beyond standard datasets.
PDF parsing, OCR, image generation, weather, geolocation, and more. General-purpose capabilities for any agent workflow.
QVeris meets your agent where it runs. REST, Python, MCP, or CLI — pick the interface that fits your stack.
Standard HTTP interface at api.qveris.ai/v1. Three
endpoints: discover, inspect, call. Works from any language, any
runtime.
Typed client library with automatic retry, session management, and async support. Install in one command and start discovering.
Native Model Context Protocol support. If your agent speaks MCP — Claude Code, Cursor, and others — QVeris exposes 10,000+ tools through an agent tool-discovery workflow.
Terminal-native workflow for scripting, CI/CD, and local development. Discover, inspect, and call without leaving the command line.
QVeris is designed for teams running agents in production — not just prototyping. Every capability call is executed in a sandboxed environment with structured output, full parameter validation, and consistent JSON responses your agent can parse reliably.
Auditability: Every call produces a unique execution ID linked to a search session and an agent session. Full trace from intent to result. Built for debugging, compliance, and cost analysis.
Observability: Monitor success rates, execution latency, and credit consumption per capability, per session, and per agent. Make data-driven decisions about which capabilities your agents depend on.
Before production, check current service terms and test availability, latency, access controls, log redaction and fallback. This page does not promise a fixed SLA or latency target.
From financial services to agentic SaaS, QVeris powers the tool-calling layer behind production AI agents.
Give trading, research, and advisory agents on-demand access to market data, fundamentals, and alternative signals through one API. No per-vendor integration.
Automate earnings analysis, peer comparison, and macro research. Agents discover and call the right data sources dynamically as research questions evolve.
Embed KYC, sanctions screening, and regulatory checks into agent workflows. Full audit trail for every call. Built for regulated environments.
Power dashboards and monitoring agents with real-time on-chain data, DeFi metrics, sentiment signals, and cross-asset market intelligence.
Build AI-native SaaS products where agents dynamically discover and call capabilities at runtime. Ship faster by outsourcing the tool-integration layer to QVeris.
General-purpose research agents that pull data from diverse sources — financial, legal, technical, and beyond — through one unified discover-inspect-call flow.
QVeris sits at a different layer of the stack. Here is how it relates to other approaches.
| Capability | QVeris | Manual API Integration | Generic API Marketplace | Simple Tool Directory |
|---|---|---|---|---|
| Tool discovery | Natural language, dynamic | Must know each API in advance | Keyword search, human-driven | Browse by category, manual |
| Cost & quality preview | Cost, latency, success rate before calling | No preview — call and see | Pricing page, not programmatic | Not available |
| Unified protocol | One API for all capabilities | N different APIs, auth, schemas | Aggregated, but limited depth | No protocol — links only |
| Provider transparency | Full provider visibility per capability | Full visibility | Often opaque | Listed but unverified |
| Agent-native design | Built for agents from day one | Built for human developers | Built for human developers | Built for human browsing |
| Audit trail | execution_id, search_id, session_id | Varies by provider | Limited to billing logs | None |
| MCP support | Native MCP server | None | None | None |
/discover endpoint. QVeris returns ranked capability
matches with cost, latency, and success rate. Your agent then
inspects and calls the chosen capability — all through one
protocol. No per-API integration code required.
pip install qveris before installation, or use the REST API. Discover and inspect first, then check permissions and cost; Playground execution requirements follow the current app.Discover and Inspect are free. Receive 1,000 one-time signup credits after verification; buy 10,000 credits for $19. Credits never expire, with no monthly fees or auto-renewal. Check the selected tool before a live call.
基础设施从第一天起就设计用于连接 Agent 与经过验证的真实世界能力。
现代 AI Agent 需要调用外部工具完成实际工作——市场数据、KYC 检查、文档解析、天气 API 等数千种。但每种工具都有各自的 API、认证方式、速率限制、错误处理和计费。集成少数几个尚可管理,集成几十个则成为拖慢团队的维护负担。
QVeris 通过一种 发现优先架构。您的 Agent 用自然语言描述所需能力,QVeris 从多个已验证提供商的 10,000+ 经过验证的工具中找出最佳匹配。一个协议。一个 API 密钥。减少每个提供商的集成工作。
它不是 LLM。不是 Agent 框架。它是将 Agent 连接到真实世界的路由层——发现、检查、调用,全部在一个统一流程中。
三步完成。发现和检查始终免费。仅在您的代理发起调用时消耗积分。
您的 Agent 提交自然语言查询——"今日标普500涨跌股"、"对此实体进行 KYC 检查"或"从该 PDF 提取表格"。QVeris 搜索 10,000+ 项能力,返回排序列表,每项标注预估成本、平均执行时间、历史成功率和提供商名称。无需硬编码端点,无需预注册。
在提交前,您的 Agent 检查任何候选能力的完整参数模式、使用示例、计费规则和实时质量指标。并列比较多个能力,选择最适合任务的一个。零成本、零风险。
您的 Agent 用结构化参数调用所选能力。QVeris 在沙箱环境中执行,返回结构化 JSON——结果负载、唯一执行 ID、计费详情和剩余信用余额。每次调用从 Agent 到执行全程可追溯。
从金融类能力到通用开发者工具,均来自不断增长的提供商网络。
涵盖股票、外汇、商品和指数的实时及历史市场数据。专为量化工作流和交易 Agent 构建。
收益数据、分析师共识、估值模型和基本面。为你的研究代理提供完整的数据基础。
KYC验证、制裁筛查和监管数据。专为需要合规感知能力的金融科技代理而构建。
区块链数据、DeFi指标、稳定币流动和钱包智能。支持加密和传统市场工作流。
新闻情绪、社交媒体分析、事件驱动指标和宏观经济意外数据。超越标准数据集。
PDF解析、OCR、图像生成、天气、地理位置等。适用于任何代理工作流的通用能力。
QVeris在代理运行的地方与其对接。REST、Python、MCP或CLI——选择适合你技术栈的接口。
QVeris专为在生产环境中运行代理的团队设计,而非仅用于原型开发。每次能力调用都在沙箱环境中执行,提供结构化输出、完整参数验证和一致的JSON响应,你的代理可可靠解析。
可审计性: 每次调用生成一个唯一的执行ID,关联到搜索会话和代理会话。从意图到结果的完整追踪。专为调试、合规和成本分析而构建。
可观测性: 监控每个能力、每个会话和每个代理的成功率、执行延迟和信用消耗。基于数据决定你的代理依赖哪些能力。
生产接入前应核对当前服务条款,并实测可用性、延迟、权限控制、日志脱敏和故障回退;本文不承诺固定 SLA 或延迟指标。
从金融服务到智能体SaaS,QVeris为生产级AI Agent背后的工具调用层提供动力。
通过一个API为交易、研究和咨询代理提供按需访问市场数据、基本面和另类信号的能力。无需逐一集成供应商。
自动化收益分析、同行比较和宏观研究。代理随着研究问题的演变动态发现并调用正确的数据源。
将KYC、制裁筛查和监管检查嵌入代理工作流。每次调用都有完整审计追踪。专为受监管环境构建。
用实时链上数据、DeFi指标、情绪信号和跨资产市场智能驱动仪表盘和监控代理。
构建 AI 原生 SaaS 产品,让智能体在运行时动态发现和调用能力。将工具集成层外包给 QVeris,加速交付。
通用研究智能体,通过统一的发现-检查-调用流程,从金融、法律、技术等多种来源获取数据。
QVeris 位于技术栈的不同层级。以下说明它与其他方案的关系。
| 能力 | QVeris | 手动API集成 | 通用 API 市场 | 简单工具目录 |
|---|---|---|---|---|
| 工具发现 | 自然语言,动态 | 必须预先了解每个 API | 关键词搜索,人为驱动 | 按类别手动浏览 |
| 成本与质量预览 | 调用前了解成本、延迟、成功率 | 无预览 — 调用后才知道 | 定价页面,非程序化 | 不可用 |
| 统一协议 | 单一 API 覆盖所有能力 | N种不同API、认证、模式 | 聚合但深度有限 | 无协议——仅链接 |
| 提供商透明度 | 每个功能的全提供商可见性 | 完全可见 | 通常不透明 | 已列出但未验证 |
| Agent 原生设计 | 从第一天起为智能体构建 | 为人类开发者构建 | 为人类开发者构建 | 为人类浏览构建 |
| 审计跟踪 | execution_id, search_id, session_id | 因提供商而异 | 仅限于计费日志 | 无 |
| MCP 支持 | 原生MCP服务器 | 无 | 无 | 无 |
/discover端点。QVeris 返回匹配能力及成本、延迟、成功率等检查信息;Agent 再检查和调用选定能力。具体字段与接入要求以当前接口契约为准。pip install qveris 后再安装或改用 REST API。先发现并检查能力,再确认权限与费用;Playground 的执行要求以当前页面为准。Model routing for compatibility and fallback checks.用于兼容性与故障回退检查的模型路由。
Official documentation官方文档OpenRouter provider detailsOpenRouter 服务商详情
