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Glama
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Server Details

Design, save, and run outcome-aligned AI workflows and verifiers, with reliable image output.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Repository
Goodeye-Labs/goodeye-cli
GitHub Stars
4

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

Full call logging

Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.

Tool access control

Enable or disable individual tools per connector, so you decide what your agents can and cannot do.

Managed credentials

Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.

Usage analytics

See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.

100% free. Your data is private.
Tool DescriptionsA

Average 4.3/5 across 72 of 72 tools scored. Lowest: 2.9/5.

Server CoherenceA
Disambiguation5/5

Every tool targets a distinct resource-action pair, with names like delete_image, deploy_verifier, and grant_workflow leaving no ambiguity. Overlap is virtually nonexistent despite the large number of tools.

Naming Consistency5/5

All tools follow a strict verb_noun pattern in snake_case, e.g., accept_invitation, archive_template, revoke_api_key. The naming convention is uniform and predictable across the entire set.

Tool Count2/5

With 72 tools, the count far exceeds the recommended 3–15 range. While the platform is feature-rich, the sheer number may overwhelm agents and suggests insufficient consolidation.

Completeness4/5

The tool surface covers most CRUD operations for templates, workflows, images, verifiers, and teams. However, the invitation lifecycle lacks a 'send_invitation' tool, which is a notable omission.

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