AI Agent Tool Platform
for MCP and API Calls
QVeris helps AI agents discover, inspect, and call MCP tools, external APIs, live data, and real-world services through one unified protocol.
Your agent describes what it needs in natural language. QVeris searches 10,000+ capabilities and returns ranked matches with cost, latency, and success rate.
Review the full parameter schema, billing rules, and quality metrics of any capability before committing. Zero-cost decision-making.
Execute through a sandboxed environment. Structured JSON response with execution ID, billing details, and credit balance — fully auditable.
Built for production AI agent tool workflows
Infrastructure designed to connect agents with MCP tools, verified APIs, live data, and real-world capabilities.
What is an AI agent tool platform?
An AI agent tool platform gives agents a reliable way to find and call external capabilities: market data, KYC checks, document parsing, financial APIs, MCP servers, and thousands more. Without a tool platform, each API brings its own authentication, schema, rate limit, error handling, and billing model. Integrating a handful is manageable. Integrating dozens becomes 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, APIs, data sources, and MCP-compatible capabilities across multiple providers. One protocol. One API key. Less per-provider integration work.
It is not an LLM and not a generic agent framework. It is the tool layer that connects agents to the real world — discover, inspect, and call, all in one unified flow.
Router
How QVeris tool calling works
Three steps for AI agent tool calling. Discovery and inspection are always free. You only spend credits when your agent makes a call.
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.
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.
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.
10,000+ tools, APIs, and live data capabilities
From finance-related capabilities to general developer tools, QVeris gives AI agents one searchable platform for real-world execution.
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.
MCP, REST API, Python SDK, and CLI in one platform
QVeris meets your agent where it runs. Use the MCP server for compatible clients, the REST API for production systems, the Python SDK for agent code, or the CLI for local workflows.
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.
Built for production AI agent infrastructure
QVeris is designed for teams running agents in production — not just prototyping. Every tool 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.
AI agent tool platform use cases
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.
AI agent tool platform vs API integration
QVeris sits at a different layer of the stack: it is a discovery, inspection, and calling platform for tools, APIs, MCP capabilities, and live data.
| 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 an AI agent tool platform?
How does QVeris connect my AI agent to external APIs and MCP tools?
/discover endpoint. QVeris returns ranked capability matches with cost, latency, provider notes, and success rate. Your agent then inspects and calls the chosen capability through one protocol.
How is QVeris different from LLM function calling?
Is QVeris an MCP tool platform?
How much does QVeris cost?
What kind of capabilities does QVeris provide?
Is QVeris suitable for production use?
How do I start using QVeris with my AI agent?
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 one platform for tools and data
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.