docs-mcp-server MCP Server

Created By
xinlei413a year ago
Overview

What is DOC-Server-MCP?

DOC-Server-MCP is a Model Context Protocol (MCP) server designed for fetching, processing, indexing, and searching documentation for various software libraries and packages.

How to use DOC-Server-MCP?

To use DOC-Server-MCP, you can deploy it using Docker or npx. Configure your environment variables, including your OpenAI API key, and run the server to start scraping and searching documentation.

Key features of DOC-Server-MCP?

  • 🌐 Versatile Scraping: Fetch documentation from diverse sources like websites, GitHub, npm, PyPI, or local files.
  • 🧠 Intelligent Processing: Automatically split content semantically and generate embeddings using various models.
  • 💾 Optimized Storage: Utilize SQLite for efficient vector storage and full-text search.
  • 🔍 Powerful Hybrid Search: Combine vector similarity and full-text search for relevant results.
  • ⚙️ Asynchronous Job Handling: Efficiently manage scraping and indexing tasks.
  • 🐳 Simple Deployment: Quick setup using Docker or npx.

Use cases of DOC-Server-MCP?

  1. Scraping and indexing documentation for software libraries.
  2. Searching documentation across different library versions.
  3. Managing documentation for various programming languages and frameworks.

FAQ from DOC-Server-MCP?

  • Can DOC-Server-MCP scrape documentation from any website?

Yes! It can fetch documentation from various sources including websites, GitHub, npm, and more.

  • Is DOC-Server-MCP free to use?

Yes! The server is open-source and free to use.

  • How do I deploy DOC-Server-MCP?

You can deploy it using Docker or npx, following the setup instructions provided in the documentation.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
xinlei413
Star
0
Language
TypeScript
License
MIT license

Recommend Servers

View All
Docwand

14 hours ago
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

14 hours ago