Connect agents to MCP, OpenAPI and GraphQL tools through Executor’s permission-aware execution gateway.
Executor gives AI agents a common route to external tools. It normalises MCP servers, OpenAPI services, GraphQL endpoints and custom integrations behind an execution interface. Instead of loading every tool definition into a conversation, an agent can discover relevant capabilities and execute a small TypeScript workflow.
The gateway separates tool discovery from execution. Search and description operations help the agent identify what is available, while the execution sandbox runs the requested sequence. This design can reduce the amount of tool metadata needed in an agent’s context without eliminating the need to understand each action.
Credential injection happens outside the sandbox according to the product’s architecture. Approval controls distinguish potentially destructive operations using information such as HTTP methods, GraphQL mutations and MCP hints. Administrators still need to inspect imported definitions and configure sensible access boundaries.
Executor offers desktop applications for macOS, Windows and Linux, a command-line route and hosted cloud operation. Its desktop, server and SDK components are described as MIT-licensed. Teams can evaluate self-hosting when they need direct control over the execution environment.
The published free cloud tier includes three members and a monthly execution allowance. Team pricing is per member with a trial, while enterprise options add controls such as SSO, provisioning and dedicated deployment. Hosted capabilities and local software should be compared separately when planning a rollout.
Start with read-only tools and a narrow credential scope. Inspect the available operations, test approval behaviour and confirm that failures are visible to the calling agent. Only enable consequential writes after reviewing permissions, action semantics and the organisation’s recovery procedures.
