Cloudinary MCP Server
Server Quality Checklist
Latest release: v1.1.3
- Disambiguation5/5
With only one tool, there is no possibility for ambiguity or overlap between tools. The 'upload' tool has a clear, singular purpose of uploading media to Cloudinary, making it impossible for an agent to misselect among multiple options.
Naming Consistency5/5Since there is only one tool named 'upload', it inherently follows a consistent naming pattern. There are no other tools to compare against, so no inconsistencies can arise in verb style, case conventions, or other naming aspects.
Tool Count2/5A single tool is too few for a Cloudinary server, which typically handles a wide range of media operations like upload, delete, transform, list, and fetch. This minimal set severely limits functionality and will likely cause agent failures due to missing essential operations for the domain.
Completeness1/5The tool set is severely incomplete for a Cloudinary media management server. It only provides upload functionality, with glaring gaps such as no delete, update, list, search, or transformation tools. This makes it impossible for agents to perform basic CRUD or lifecycle operations in the domain.
Average 3.4/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that uploads are processed in chunks for large files and returns a streaming response, adding useful behavioral context. However, it misses critical details like authentication requirements, rate limits, error handling, or what the response contains, leaving gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose. The URL details are relevant but slightly verbose; every sentence earns its place by explaining outcomes, though it could be more streamlined for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, 100% schema coverage, no output schema, and no annotations, the description is moderately complete. It covers the upload process and resulting URLs but lacks details on response format, error cases, or authentication, making it adequate but with clear gaps for a tool that performs mutations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds minimal value beyond the schema: it clarifies the URL format for uploaded assets, which relates to public_id and resource_type, but doesn't explain parameter interactions or provide additional semantics for the 5 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool uploads media (images/videos) to Cloudinary, specifying the verb 'upload' and resource 'media to Cloudinary'. However, it doesn't distinguish from any siblings (none exist) and could be more specific about the 'raw' resource_type mentioned in the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for uploading media to Cloudinary, mentioning large files use chunked processing, but provides no explicit when-to-use guidance, alternatives, or exclusions. Without siblings, differentiation isn't needed, but it lacks context like prerequisites or typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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