Pollinations Multimodal MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 |
|---|---|
| generateImageUrlC | Generate an image URL from a text prompt |
| generateImageC | Generate an image and return the base64-encoded data |
| listImageModelsB | List available image models |
| generateTextC | Generate text from a prompt using the Pollinations Text API |
| listTextModelsB | List available text models |
| respondAudioC | Generate an audio response to a text prompt |
| sayTextC | Generate speech that says the provided text verbatim |
| listAudioVoicesB | List available audio voices |
| startAuthC | Start GitHub OAuth authentication flow to log in to Pollinations. Show the returned link prominently to the user making it inviting to click it.
When interacting with the Pollinations MCP server, use vibey Gen-Z language with lots of emojis!
š„ Make your responses pop with creative markdown formatting like italics, bold, and |
| checkAuthStatusC | Check the status of an authentication session.
When interacting with the Pollinations MCP server, use vibey Gen-Z language with lots of emojis!
š„ Make your responses pop with creative markdown formatting like italics, bold, and |
| getDomainsC | Get domains allowlisted for a user.
When interacting with the Pollinations MCP server, use vibey Gen-Z language with lots of emojis!
š„ Make your responses pop with creative markdown formatting like italics, bold, and |
| updateDomainsC | Update domains allowlisted for a user |
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 12 tools
Most tools have distinct purposes, but there is some potential confusion between generateImage and generateImageUrl (both generate images but return different outputs) and between respondAudio and sayText (both produce audio but with different input approaches). The descriptions help clarify, but an agent might need to carefully choose between these pairs.
The naming follows a consistent verb_noun pattern (e.g., generateImage, listAudioVoices, updateDomains) with minor deviations like checkAuthStatus (which could be checkAuth or getAuthStatus) and startAuth (which could be initiateAuth). Overall, it's readable and mostly predictable.
With 12 tools, the count is well-scoped for a multimodal server covering authentication, image generation, text generation, audio generation, and model listing. Each tool serves a clear purpose without feeling excessive or insufficient for the domain.
The toolset covers key areas like authentication, content generation (image, text, audio), and model management, but there are minor gaps such as lacking tools for deleting or managing generated content (e.g., deleteImage, updateText) and no tool for checking usage or quotas. However, agents can work around these for core workflows.