Capability Routing Network

The Capability Routing Network
for AI Agents

QVeris helps AI agents discover, inspect, and call verified real-world tools, APIs, live data, and external services through one unified protocol.

Always Free
🔍
Discover

Your agent describes what it needs in natural language. QVeris searches 10,000+ capabilities and returns ranked matches with cost, latency, and success rate.

Always Free
⚙️
Inspect

Review the full parameter schema, billing rules, and quality metrics of any capability before committing. Zero-cost decision-making.

Credits-Based
Call

Execute through a sandboxed environment. Structured JSON response with execution ID, billing details, and credit balance — fully auditable.

Built for production AI agent workflows

Infrastructure designed from day one to connect agents with verified real-world capabilities.

10,000+
Verified capabilities across 15+ categories
Unified
One protocol for every tool, API, and data source
Multi-Interface
REST API, Python SDK, MCP Server, and CLI
Production
99.99% uptime, sub-500ms p95, RBAC, sandboxed

A capability routing layer for AI agents

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.

QVeris
Router
Agent
APIs
Data
Tools

Discover. Inspect. Call.

Three steps. Discovery and inspection are always free. You only spend credits when your agent makes a call.

1

Discover

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.

2

Inspect

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.

3

Call

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.

15+ categories, 10,000+ verified capabilities

From finance-related capabilities to general developer tools, sourced from a growing provider network.

📈

Finance Data

Real-time and historical market data across equities, FX, commodities, and indices. Built for quantitative workflows and trading agents.

📊

Investment Research

Earnings data, analyst consensus, valuation models, and fundamentals. Give your research agent a complete data foundation.

🛡️

Risk & Compliance

KYC verification, sanctions screening, and regulatory data. Built for fintech agents needing compliance-aware capabilities.

Crypto & On-Chain Data

Blockchain data, DeFi metrics, stablecoin flows, and wallet intelligence. Supports crypto and traditional market workflows.

📡

Alternative Signals

News sentiment, social media analytics, event-driven indicators, and macroeconomic surprise data. Go beyond standard datasets.

🔧

Developer Tools

PDF parsing, OCR, image generation, weather, geolocation, and more. General-purpose capabilities for any agent workflow.

Integrate your way — no framework lock-in

QVeris meets your agent where it runs. REST, Python, MCP, or CLI — pick the interface that fits your stack.

Developer integration architecture showing REST API, Python SDK, MCP Server connecting through QVeris to APIs, Tools, and Live Data
🌐

REST API

Standard HTTP interface at api.qveris.ai/v1. Three endpoints: discover, inspect, call. Works from any language, any runtime.

🐍

Python SDK

Typed client library with automatic retry, session management, and async support. Install in one command and start discovering.

🔖

MCP Server

Native Model Context Protocol support. If your agent speaks MCP — Claude Code, Cursor, and others — QVeris appears as an MCP server with 10,000+ discoverable tools.

⌨️

CLI

Terminal-native workflow for scripting, CI/CD, and local development. Discover, inspect, and call without leaving the command line.

Production workflow architecture showing Validate, Execute, and Audit pipeline stages

Built for production agent workflows

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.

Reliability: 99.99% uptime with sub-500ms p95 latency. RBAC access controls. No single-provider dependency — capabilities are sourced from a growing provider network.

What teams are building with QVeris

From financial services to agentic SaaS, QVeris powers the tool-calling layer behind production AI agents.

💹

Finance 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.

📄

Investment Research Automation

Automate earnings analysis, peer comparison, and macro research. Agents discover and call the right data sources dynamically as research questions evolve.

Compliance Workflows

Embed KYC, sanctions screening, and regulatory checks into agent workflows. Full audit trail for every call. Built for regulated environments.

📡

Market & Crypto Intelligence

Power dashboards and monitoring agents with real-time on-chain data, DeFi metrics, sentiment signals, and cross-asset market intelligence.

🏗️

Agentic SaaS Products

Build AI-native SaaS products where agents dynamically discover and call capabilities at runtime. Ship faster by outsourcing the tool-integration layer to QVeris.

🧠

Research & Analysis Agents

General-purpose research agents that pull data from diverse sources — financial, legal, technical, and beyond — through one unified discover-inspect-call flow.

How QVeris compares

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

Frequently asked questions

What is a capability routing network?
A capability routing network is an infrastructure layer that sits between AI agents and external tools, APIs, and data sources. Instead of hardcoding each integration, the agent describes what it needs in natural language, and the network discovers, inspects, and routes the call to the best-matching capability. QVeris is the first capability routing network built specifically for AI agents, with 10,000+ verified capabilities across 15+ categories.
How does QVeris connect my AI agent to external APIs?
QVeris provides a unified REST API, Python SDK, MCP server, and CLI. Your agent sends a natural-language query to the /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.
How is QVeris different from LLM function calling?
LLM function calling lets a model invoke tools you have pre-registered — but you still need to code and maintain every integration yourself. QVeris maintains 10,000+ pre-verified integrations across multiple verified providers, and lets your agent discover them dynamically at runtime. Function calling handles the LLM-to-tool handoff; QVeris handles the tool-to-real-world routing.
How does QVeris work with MCP servers?
QVeris ships a native MCP server. If your agent or coding environment supports the Model Context Protocol — including Claude Code, Cursor, and other MCP-compatible platforms — QVeris appears as an MCP server exposing 10,000+ discoverable tools. You configure the endpoint once and start discovering capabilities immediately.
How much does QVeris cost?
Discovery and inspection are always free. You only pay when your agent makes a call. The Free tier includes 1,000 credits on signup plus 100 credits per day. The Pro plan is $19/month for 10,000 credits. Scale On-Demand lets you pay as you go from $1, with credits that never expire. Typical calls cost 1–15 credits depending on the capability.
What kind of capabilities does QVeris provide?
QVeris covers 15+ categories: quantitative trading data, macro and fixed income, risk and compliance (KYC, sanctions screening), investment research, crypto and digital assets, alternative signals (news sentiment, social data), PDF parsing, OCR, image generation, weather, geolocation, and more — 10,000+ individual capabilities sourced from a growing provider network.
Is QVeris suitable for production use?
Yes. QVeris operates with a 99.99% uptime, sub-500ms p95 latency, RBAC access controls, sandboxed execution, and full audit trails for every call. It is designed for teams running AI agents in production, with structured JSON output, consistent schemas, and session-scoped tracing for debugging and compliance.
How do I start using QVeris with my AI agent?
Sign up for a free account at qveris.ai to get 1,000 starter credits. Retrieve your API key from the dashboard. Install the Python SDK (pip install qveris) or call the REST API directly. Run your first discover query. You can also try the Playground with no account required to explore live capabilities immediately.

Give your agent the tools it needs

Sign up for free and start with 1,000 credits. Discover, inspect, and call 10,000+ verified capabilities through one unified protocol. No lock-in. Credits never expire.