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Goodeye MCP Server

@Goodeye-Labs

Repository

Basic information

Category

Developer Tools

Transports

stdio

Author

Goodeye-Labs

Submitted by

Randy Olson

About Goodeye MCP Server

Outcome-aligned AI workflow registry. Design and run AI workflows with verifiers that align an agent to measurable outcomes, with reliable image output.

#ai-workflows#ai-agents#verifiers#image-generation#workflow-automation#developer-tools

Goodeye MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "goodeye": {
      "type": "http",
      "url": "https://mcp.goodeye.dev/mcp"
    }
  }
}

Goodeye MCP Server tools

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Overview

What is Goodeye?

Goodeye is an outcome-aligned AI workflow registry. It enables designing AI workflows paired with verifiers that score an agent against a measurable result, then running them from an agent or the CLI. Reliable image output is built in.

How to use Goodeye?

Connect to Goodeye’s remote MCP server via Streamable HTTP using the provided JSON configuration (URL https://mcp.goodeye.dev/mcp). Authenticate with OAuth or by passing a good_live_ API key as a Bearer token. Alternatively, install the CLI tool with uv tool install goodeye.

Key features of Goodeye

  • Outcome-aligned AI workflow registry with verifiers.
  • Score agents against measurable results.
  • Run workflows from an agent or CLI.
  • Built-in reliable image output.

Use cases of Goodeye

  • Designing AI workflows that are automatically scored on outcomes.
  • Running verifiable agent tasks from a command-line interface.
  • Integrating outcome-based evaluation into existing AI pipelines.

Frequently asked questions

1

How do I authenticate with the Goodeye MCP server?

Sign in with OAuth, or pass a `good_live_` API key as a Bearer token in the request.

2

What transport protocol does Goodeye use?

Goodeye supports remote MCP over Streamable HTTP.

3

How can I install the Goodeye CLI?

Install it with `uv tool install goodeye`.

4

Where can I find the workflow catalog and documentation?

The catalog is at https://goodeye.dev and full documentation is at https://goodeye.dev/docs.

Comments

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