refinery-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| APIFY_TOKEN | Yes | Your Apify API token | |
| REFINERY_ACTOR_ID | No | The ID of the Refinery Apify Actor | larelabs/refinery-html-to-llm-cleaner |
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| clean_urlC | Fetch a URL with the Refinery Apify actor and return clean LLM-ready text plus word_count. |
| clean_htmlB | Clean raw HTML that your agent, crawler, or browser session already fetched. |
| estimate_savingsA | Estimate token savings from raw HTML vs cleaned text without making an Apify call. |
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 targets a distinct input source: raw HTML, URL, or estimation, with no functional overlap.
All tools use consistent verb_noun snake_case pattern (clean_html, clean_url, estimate_savings).
Three tools is ideal for this narrow domain of HTML cleaning and token savings estimation.
The tool set covers all core operations: cleaning input text, fetching and cleaning a URL, and estimating token savings without a call.