Pollinations 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 |
|---|---|
| generate_imageC | 使用Pollinations.ai生成图像 |
| download_imageC | 下载Pollinations.ai生成的图像到本地文件 |
| generate_textC | 使用Pollinations.ai生成文本 |
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 3 tools
Each tool has a clearly distinct purpose: download_image handles saving generated images locally, generate_image creates images, and generate_text creates text. There is no overlap or ambiguity between these three functions.
All tools follow a consistent verb_noun pattern (download_image, generate_image, generate_text) with no deviations in style or convention. The naming is predictable and readable throughout.
With only 3 tools, the server feels thin for a generative AI service, potentially lacking operations like listing, updating, or deleting generated content. However, it covers core generation and download functions adequately.
The tools provide basic generation and download capabilities, but there are notable gaps: no tools for managing or querying existing generations (e.g., list, delete, update), and no text download equivalent. This limits workflow completeness.