Logo.dev MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LOGO_DEV_API_KEY | Yes | Your Logo.dev API key (get one at https://logo.dev) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_logosA | Search for company logos by brand name or company name. Returns a list of matching companies with their domains and logo URLs. |
| get_logo_urlC | Get a direct logo image URL for a specific domain. Supports customization options like size, format, theme, and more. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: get_logo_url retrieves a specific logo for a given domain with customization options, while search_logos finds logos by brand/company name and returns a list of matches. There is no overlap or ambiguity between them.
Both tools follow a consistent verb_noun naming pattern (get_logo_url and search_logos), using snake_case throughout. The naming is predictable and readable, with no deviations in style.
With only 2 tools, the server feels thin for a logo service domain. While the tools cover basic retrieval and search, more operations like logo validation, batch processing, or metadata access could enhance completeness. The count is borderline for the apparent scope.
The server provides core lookup functionality (get and search), but there are notable gaps. For a logo service, operations like logo upload, update, deletion, or analytics are missing, limiting lifecycle coverage. Agents can work around this for basic tasks but may fail on advanced workflows.