F
licenseNot graded
qualityNot graded
maintenanceA basic example of developing and running serverless Model Context Protocol (MCP) using Netlify Functions, enabling AI agents to interact with your services via a standardized API.
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Netlify MCP Server
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TDQS
C2.4/5.0
Scored across 6 tools
Disambiguation3/5
The tools are grouped by resource type (deploy, extension, project, team, user), which provides some clarity, but the grouping approach creates ambiguity within each tool. For example, 'ntl-project-operations' bundles 9 different operations under one tool name, making it impossible for an agent to distinguish between them without reading the description. This forces the agent to parse the description to understand available actions, rather than having distinct tools for each operation.
Naming Consistency4/5
Most tools follow a consistent 'ntl-[resource]-operations' pattern (e.g., ntl-deploy-operations, ntl-project-operations), which is predictable. However, 'get-netlify-coding-context' deviates from this pattern, using a verb-noun format instead. This minor inconsistency reduces the overall naming coherence, but the majority of tools adhere to a clear convention.
Tool Count4/5
With 6 tools, the count is reasonable for a Netlify server, covering key areas like deployments, extensions, projects, teams, and users. It's slightly lean given the bundled operations, but each tool represents a logical domain, making the scope manageable. A few more tools could provide better granularity, but this is not a significant issue.
Completeness3/5
The server covers core Netlify domains (deployments, projects, teams, users, extensions) but has notable gaps. For example, there are no tools for creating or deleting deployments, managing site settings, or handling build operations. The bundled operations within tools suggest some coverage, but the surface is incomplete for full lifecycle management, which may cause agent failures in complex workflows.