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AI Agents

AI agents are first-class participants in the Convex economy. They can own accounts, hold assets, execute transactions, and contract with humans and other agents — all under the same rules, the same costs, and the same finality.

Convex doesn't distinguish between human users and autonomous agents. Every account on the network follows the same physics: deterministic execution, atomic transactions, and cryptographic authentication. This makes Convex a natural substrate for agentic systems where AI models need to interact with real economic state.

Why Convex for AI agents?​

  • Native MCP support — Convex peers ship with built-in Model Context Protocol servers, so any MCP-compatible AI agent can interact with the network out of the box
  • Deterministic execution — the CVM guarantees identical results for identical inputs, eliminating a whole class of agent coordination bugs
  • Sub-second finality — transactions settle in under a second, fast enough for real-time agent decision loops
  • Global state — agents can read the entire network state (balances, contracts, assets) with a single query, no indexers required
  • Universal asset model — one interface for fungible tokens, NFTs, and arbitrary digital assets (CAD019)
  • Economic constraints — juice pricing and memory accounting prevent runaway agents from spamming the network

Guides​

Each guide builds on the previous one, but you can jump directly to what you need:

  • MCP Integration — connect AI agents to Convex via the Model Context Protocol. Covers available tools, querying state, executing transactions, and signing approaches.
  • Account Management — create, fund, and secure agent accounts. Covers key management, controllers, and the trade-offs between full autonomy and delegated signing.
  • Agentic Economics — design economic interactions between agents. Covers direct transactions, smart contract coordination, autonomous strategies, and multi-agent architectures.

Further reading​