QVeris
Connect your AI
Ecosystem

Built together,
open by default.

QVeris is designed to work with the tools agents and developers already use. Open-source CLI, typed SDKs, MCP server, and a growing community of skill builders.

QVeris Products

Built and maintained by QVeris AI

Two first-party open-source projects for different use cases — a token-efficient CLI for agents and a multi-agent workflow engine. Both have native QVeris integration out of the box.

By QVeris AI

QVeris CLI

Zero-token tool calling for agents and developers

Discover, inspect, and call a broad catalog of real-world capabilities from the terminal. Runs as a subprocess — zero schema tokens, schemas never enter the LLM context. Interactive REPL for human exploration, --json structured output for agent automation, qveris doctor self-check, qveris usage / qveris ledger billing audit. Zero external dependencies.

  • ▸Zero schema tokens vs MCP — runs outside the LLM context, tool registries stay out of the prompt
  • ▸Interactive REPL with colored output, spinners, and codegen (curl / Python / JS)
  • ▸Agent-native: --json output, probe validation and quoting, --dry-run preview, structured exit codes
  • ▸One-line site-aware install + interactive login: curl -fsSL https://qveris.ai/cli/install | bash; then qveris login
  • ▸Session index shortcuts (30-min TTL) + qveris usage / qveris ledger for charge_outcome audit
Best for: Agents with shell access (Claude Code, OpenClaw, Hermes Agent, terminals) that need zero-schema-token tool calling, and developers who want terminal-first API discovery with built-in billing audit.
View on GitHub →
By QVeris AI

QVerisFlow

Multi-agent workflow engine powered by LangGraph + QVeris

A LangGraph-based multi-agent framework for building, visualizing, and executing complex AI workflows. Create workflows through natural language conversation or a visual canvas editor. A Meta Agent automatically analyzes tasks and generates optimal agent definitions with QVeris as the unified data and tool layer.

  • ▸Conversational workflow building — describe your need in natural language, get a working workflow
  • ▸Visual canvas editor (React + ReactFlow) with drag-and-drop, real-time state, and live execution monitoring
  • ▸Meta Agent auto-generates agent definitions and orchestration from task descriptions
  • ▸Multi-model support: Qwen, DeepSeek, GPT, GLM, Kimi, and more
  • ▸Three-layer verification: rule validation + LLM evaluation + composite checks
Best for: Developers building complex multi-agent pipelines — financial analysis, research automation, data processing — where multiple specialized agents collaborate through structured workflows.
View on GitHub →
Agent Clients

Agent Clients

Plugin + Skill

OpenClaw

The open-source AI agent client. Integrate QVeris via the official Plugin (recommended) or Skill — install with one command, then configure your API key.

GitHub →Full setup guide →
Recommended

Plugin — via ClawHub

Runtime-level tool registration. Tools stay available regardless of context length — no prompt competition, no forgetting.

1. Install
openclaw plugins install clawhub:@qverisai/qveris --accept-capabilities
Copy setup prompt
Install the QVeris plugin from ClawHub: openclaw plugins install clawhub:@qverisai/qveris --accept-capabilities, then configure plugins.allow: ["qveris"], plugins.entries.qveris: { enabled: true, config: { apiKey: "YOUR_KEY" } }, and tools.alsoAllow: ["qveris"] in openclaw.json
View on ClawHub →
Lightweight alternative

Skill — via ClawHub

Instruction-only, zero dependencies. Good for quick trials or restricted environments where npm is unavailable.

1. Install
openclaw skills install qveris-official
Copy setup prompt
Install QVeris skill: openclaw skills install qveris-official, then add "qveris-official": { "enabled": true, "apiKey": "YOUR_KEY" } to skills.entries in ~/.openclaw/openclaw.json
View on ClawHub →
MCP compatible

Cursor

AI-powered code editor. Add QVeris via MCP configuration to give Cursor agents access to a broad catalog of real-world capabilities.

Learn more →
CLI / MCP

Claude Code

Anthropic's agentic coding tool. Use QVeris CLI (recommended) or install the MCP server to extend Claude with real-world data and tools.

Learn more →
CLI / MCP

OpenCode

Open-source terminal coding agent. Add QVeris MCP to opencode.json or use the CLI for low-token tool access.

Learn more →
SDKs & Packages

SDKs & Packages

PyPI

Python SDK

v0.9.0 — pip install qveris. Full typed API surface, async support, retry logic, and streaming. The standard way to integrate QVeris in Python agents.

Learn more →
npm

npm Packages

@qverisai/sdk v0.10.0 and other packages for JavaScript/TypeScript environments. Works in Node.js, Deno, and edge runtimes.

Learn more →
MCP

@qverisai/mcp

v0.15.0 — MCP server exposing discover, inspect, probe, call plus usage_history and credits_ledger audit tools. For Cursor, Claude Desktop, and all MCP-compatible agents. Configure QVERIS_BASE_URL with the endpoint shown by this site.

Learn more →
Community & Resources

Community & Resources

Community

ClawHub Skills

Community-curated skill packs for OpenClaw and Claude. Browse, install, and share agent skills that use QVeris capabilities.

Learn more →
Open source

GitHub Organization

All QVeris open-source repositories: CLI, MCP server, Python SDK, example agents, skills, and contributing guides.

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Documentation

REST API Reference

Full Discover, Inspect, and Call endpoint documentation with request/response examples, authentication guide, and error codes.

Learn more →

Join the ecosystem

Get an API key, build with the CLI or SDK, and contribute back. Everything you build on QVeris can be shared as a skill on ClawHub.

Get started — freeGitHub →
QVeris Open Ecosystem — GitHub, ClawHub, npm, and OpenClaw Contributions