call_modelLABSCO SUMMARY
Summarizing runs on a model you point it at, not on the one you are talking to.
That is the whole design: long pages and PDFs get compressed by a separate OpenAI-compatible endpoint before they land in your assistant's context, and you choose the ratio — 0.2 means a fifth of the original. It also means a second API key of your own, and file and page content is capped at roughly 120k characters going in.
What it is
A summarization server: it fetches pages and reads files, then runs them through an OpenAI-compatible model you configure and returns the condensed version.
What you get
- Fetch a web page, optionally saving it to a txt file — scrape_webpage
- Summarize any text to a target ratio, 0.2 by default — summarize_content
- Fetch and summarize a page in one call — summarize_webpage
- Summarize a txt file or a PDF from a path — read_and_summarize_text_file, read_and_summarize_pdf_file
- Pull the parts of a document that answer a question, returned within 2k characters — topic_based_summary
- Send a prompt directly to the configured model — call_model
Requirements
An API key in OPENAI_API_KEY — MiniMax by default, with OPENAI_BASE_URL and OPENAI_MODEL pointing anywhere OpenAI-compatible. Install with uvx fullscope-mcp-server or pip install fullscope-mcp-server; version 1.0.1.
Setup effort
One command plus a key — uvx fullscope-mcp-server, then supply credentials
USE CASES
01
Reading a long article without spending the context on it
Hand over the URL and get the condensed version back at the ratio you set.
02
Getting a PDF down to the parts you need
Point at the file path; the text is extracted and summarized before it reaches the conversation.
03
Pulling only what answers your question out of a pile of material
Give it the content and the question, and it returns the relevant part within 2k characters.
04
Keeping a page for later
Scrape it and save the text to a txt file in the same call.
7 tools
Listed in project docs. Your client may show a different list.
scrape_webpagesummarize_contentsummarize_webpageread_and_summarize_text_fileread_and_summarize_pdf_filetopic_based_summaryBEFORE YOU INSTALL
What to know first
Tools you get
7 tools named in the project's documentation.
Requires
- uvx on PATH
- OPENAI_API_KEY in your environment
Where it runs
Both documented setups run the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
uvx fullscope-mcp-serverMCP Clients
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"fullscope-mcp": {
"command": "uvx",
"args": [
"fullscope-mcp-server"
],
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>",
"OPENAI_BASE_URL": "https://api.minimaxi.com/v1",
"OPENAI_MODEL": "MiniMax-M1",
"MAX_INPUT_TOKENS": "900000",
"MAX_OUTPUT_TOKENS": "8000"
}
}
}
}Claude Desktop — pip
CLAUDE DESKTOP — PIP · JSON
{
"mcpServers": {
"fullscope-mcp": {
"command": "python",
"args": [
"-m",
"fullscope_mcp_server"
],
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>",
"OPENAI_BASE_URL": "https://api.minimaxi.com/v1",
"OPENAI_MODEL": "MiniMax-M1",
"MAX_INPUT_TOKENS": "900000",
"MAX_OUTPUT_TOKENS": "8000"
}
}
}
}
