81 lines
2.0 KiB
Markdown
81 lines
2.0 KiB
Markdown
# MCP Summary Server
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An MCP (Model Context Protocol) server for document summarization that keeps full text out of the chat context window.
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## Features
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- Automatically determines whether to summarize directly or use chunked summarization
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- All processing happens server-side
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- Returns only the summary to the client
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- Configurable chunking parameters
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- Bearer token authentication (optional)
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## Setup
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### Environment Variables
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Copy `.env.example` to `.env` and configure:
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```bash
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cp .env.example .env
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```
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| Variable | Default | Description |
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|----------|---------|-------------|
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| PORT | 8080 | HTTP server port |
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| API_KEY | (empty) | Bearer token for authentication |
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| OPENAPI_URL | http://localhost:8080/v1 | LLM API endpoint |
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| OPENAPI_API_KEY | (empty) | LLM API key |
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| MODEL_NAME | gpt-4o | LLM model to use |
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| CHUNK_SIZE | 4000 | Characters per chunk |
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| OVERLAP | 200 | Characters of overlap between chunks |
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| TARGET_INTERMEDIATE_SUMMARY_LENGTH | 150 | Words per chunk summary |
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| MAX_DIRECT_SUMMARY_LENGTH | 100 | Max final summary length |
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| MAX_DIRECT_TEXT_LENGTH | 8000 | Max text length before chunking |
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## Running
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### Docker
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```bash
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# Build
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docker build -t mcp-summary .
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# Run with environment file
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docker run -p 8080:8080 --env-file .env mcp-summary
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# Run with inline environment variables
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docker run -p 8080:8080 \
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-e OPENAPI_URL=http://localhost:8080/v1 \
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-e OPENAPI_API_KEY=your-key \
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-e MODEL_NAME=gpt-4o \
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mcp-summary
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```
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### Python
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```bash
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pip install -r requirements.txt
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python mcp_summary_server.py
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```
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## MCP Tool
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### summarize_document
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Summarizes a document, automatically handling chunking for long text.
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**Parameters:**
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- `text` (string, required): The document text to summarize
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- `max_length` (integer, optional): Maximum summary length in words (default: 100)
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**Returns:**
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```json
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{
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"summary": "The summarized text...",
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"original_length": 12345,
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"method": "direct", // or "chunked"
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"chunks": 1 // number of chunks used
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}
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```
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