Executor: Universal MCP Gateway for AI Agents

LinkRhys SullivanTool

Executor connects OpenAPI specs, GraphQL endpoints, and MCP servers into a single MCP gateway. Instead of manually configuring credentials and tools across multiple agent clients, it exposes a single execution tool that retrieves integrations on demand inside a sandboxed environment.

Key points

  1. Serves as a unified gateway connecting OpenAPI, GraphQL, and MCP endpoints to any MCP client (such as Claude Code or Cursor).
  2. Massively cuts prompt context usage: reduces over a thousand tool schemas (~278,800 tokens) down to a single meta-tool (~1,044 tokens) that discovers functions at runtime.
  3. Keeps credentials out of LLM contexts by injecting authentication host-side rather than passing tokens into the sandboxed runtime.
  4. Enforces source-level safety policies, automatically distinguishing safe reads from destructive calls (GET vs. DELETE, GraphQL mutations, destructiveHint).
  5. Available across multiple deployment targets: hosted Cloud, Desktop app, headless CLI, or self-hosted Docker container.

Why it matters

As developers adopt multiple AI coding assistants, managing API keys across separate tools creates credential sprawl and consumes significant prompt space. A centralized gateway standardizes tool access while significantly reducing context token usage.

Analysis

Executor tackles two of the main friction points in production agent workflows: context bloat and credential fragmentation. Rather than injecting exhaustive API schemas into the system prompt, it provides a code-execution paradigm where tools are queried dynamically. Keeping credentials outside the sandbox and prompt context reinforces secure-by-default execution in corporate environments.

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Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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