Executor is an integration layer for AI agents that lets them call any OpenAPI, MCP, GraphQL, or custom JavaScript functions in a secure environment.
The problem Executor solves is the fragmentation of integrations across multiple AI agents. Each agent typically requires its own copy of every integration, with credentials and policies configured separately in each place. Executor centralizes this by acting as a single catalog that any MCP-compatible agent can access. You configure an integration once with its authentication and per-tool policies, then all your agents share that same setup over MCP. The tool supports MCP servers, OpenAPI specs, GraphQL APIs, and Google Discovery APIs as first-class integration types, with an open plugin system for custom integrations.
Executor suits teams using multiple AI agents who want to avoid duplicating integration setup across Claude Code, Cursor, ChatGPT, and similar tools. It works best when you need consistent policies and authentication across agents, and when you want integrations to live in one place rather than scattered across client configurations. The tool offers multiple deployment options: Executor Cloud for hosted setup with no installation, a local CLI for Node.js environments, a desktop app, or self-hosted deployment on Docker or Cloudflare. The README does not compare Executor to alternative solutions.
The project maintains active engagement through its Discord community channel and provides comprehensive documentation including a setup prompt that agents themselves can follow to configure Executor end-to-end. Development activity shows ongoing refinement of the integration model, with clear conceptual documentation and multiple deployment pathways being actively supported. The tool is packaged to work the same way across all its runtime options, suggesting consistent maintenance of feature parity across different installation methods.
