# 📚 LiveDocs MCP

> **Give your AI the docs it actually needs — fresh from the source, every time.**

![Python](https://img.shields.io/badge/Python-3.11%2B-3776AB?logo=python&logoColor=white)
![FastMCP](https://img.shields.io/badge/FastMCP-4.x-blueviolet)
![License](https://img.shields.io/badge/License-MIT-green)
![Libraries](https://img.shields.io/badge/Libraries-45%2B-orange)
![Deploy](https://img.shields.io/badge/Deploy-Render-46E3B7?logo=render)

---

## 🔎 The Problem

Every AI engineer has hit this wall:

> _"Claude is giving me the LangChain v0.1 API but we're on v0.3"_
> _"Why is the OpenAI example broken — oh, they changed the client in v1.0"_
> _"The CrewAI docs changed again, my code is outdated"_

LLMs are trained on a **snapshot of the internet**. Documentation moves fast. Your AI assistant doesn't.

**LiveDocs MCP bridges that gap.** It connects Claude (or any MCP-compatible AI) directly to official documentation websites in real time — no stale training data, no hallucinated APIs.

---

## ✨ Features

| Feature                    | Description                                                    |
| -------------------------- | -------------------------------------------------------------- |
| 🔴**Live Docs**            | Fetches directly from official docs — always current           |
| 📦**45+ Libraries**        | Every major AI engineering library covered                     |
| ⚡**Smart Cache**          | 24-hour TTL cache — fast repeat queries, no wasted API calls   |
| 🔁**Multi-Library Search** | Compare docs across frameworks side-by-side                    |
| 💻**Code Extraction**      | Hunts for code-block-rich pages automatically                  |
| 🔢**Version-Aware**        | Pin to a specific version (e.g.`v0.2`, `2.1.0`)                |
| 🔑**BYOK**                 | Bring Your Own Serper API key per request                      |
| 🌐**Remote-Ready**         | Deploy as HTTP/SSE server — share one URL with your whole team |

---

## 📦 Supported Libraries (45+)

<details>
<summary><strong>🤖 LLM Providers</strong></summary>

| Key         | Library       | Description                             |
| ----------- | ------------- | --------------------------------------- |
| `openai`    | OpenAI        | GPT-4o, embeddings, DALL·E, Whisper     |
| `anthropic` | Anthropic     | Claude API — messages, tool use, vision |
| `groq`      | Groq          | Ultra-fast LLM inference                |
| `mistral`   | Mistral AI    | Mixtral, Mistral-7B                     |
| `cohere`    | Cohere        | Command R, Embed, Rerank                |
| `together`  | Together AI   | Open-source model inference             |
| `replicate` | Replicate     | Run open-source models via API          |
| `google_ai` | Google Gemini | Gemini Pro, Flash, embeddings           |

</details>

<details>
<summary><strong>🔗 LLM Frameworks</strong></summary>

`langchain` · `langgraph` · `langsmith` · `llama_index` · `haystack` · `dspy`

</details>

<details>
<summary><strong>🕵️ Agent Frameworks</strong></summary>

`crewai` · `autogen` · `semantic_kernel` · `smolagents` · `pydantic_ai`

</details>

<details>
<summary><strong>🗄️ Vector Databases</strong></summary>

`pinecone` · `weaviate` · `chromadb` · `qdrant` · `milvus` · `pgvector`

</details>

<details>
<summary><strong>🧠 ML Models & Embeddings</strong></summary>

`huggingface` · `sentence_transformers`

</details>

<details>
<summary><strong>📊 Observability & MLOps</strong></summary>

`langsmith` · `weights_biases` · `mlflow`

</details>

<details>
<summary><strong>🌐 Web Frameworks</strong></summary>

`fastapi` · `pydantic` · `django` · `flask`

</details>

<details>
<summary><strong>💾 Databases & ORMs</strong></summary>

`sqlalchemy` · `supabase` · `prisma` · `redis`

</details>

<details>
<summary><strong>🐍 Python & DevOps</strong></summary>

`uv` · `ruff` · `pytest` · `docker` · `pandas` · `polars`

</details>

---

## 🛠️ MCP Tools Reference

| Tool                                                  | Description                              |
| ----------------------------------------------------- | ---------------------------------------- |
| `get_docs(query, library, version?, serper_api_key?)` | Fetch live docs for any library          |
| `search_docs_multi(query, libraries[])`               | Search across multiple libraries at once |
| `get_code_examples(query, library, language?)`        | Targeted code snippet extraction         |
| `list_libraries(category?)`                           | Browse all 45+ supported libraries       |
| `cache_stats()`                                       | View cache hits / entries / TTL          |

---

## 🚀 Quick Start

### Option 1 — Remote Server (Recommended — no install needed)

Add this to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "live-docs": {
      "url": "https://live-docs-mcp.onrender.com/sse"
    }
  }
}
```

> **Config file location:**
>
> - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
> - Windows: `%APPDATA%\Claude\claude_desktop_config.json`

---

### Option 2 — Local (Self-Hosted)

**Prerequisites:** Python 3.11+, [uv](https://docs.astral.sh/uv)

```bash
# 1. Clone
git clone https://github.com/NoumanZahid-85/live-docs-mcp.git
cd live-docs-mcp

# 2. Install dependencies
uv sync

# 3. Configure
cp .env.example .env
# Edit .env and add your SERPER_API_KEY (free at https://serper.dev)

# 4. Test the CLI client
uv run python mcp_client.py
# > Library: openai
# > Query: streaming chat completion
```

**Claude Desktop config (local stdio):**

```json
{
  "mcpServers": {
    "live-docs": {
      "command": "uv",
      "args": ["run", "python", "mcp_server.py"],
      "cwd": "/absolute/path/to/live-docs-mcp",
      "env": {
        "SERPER_API_KEY": "your_serper_api_key"
      }
    }
  }
}
```

---

## 🌐 Deploy Your Own Instance

### Render (Free Tier)

[![Deploy to Render](https://render.com/images/deploy-to-render-button.svg)](https://render.com/deploy)

1. Fork this repo
2. Connect to [Render](https://render.com) → **New Web Service** → select your fork
3. Set environment variable `SERPER_API_KEY` in the Render dashboard
4. Render auto-detects `render.yaml` and deploys

Your server will be live at `https://your-service.onrender.com/sse`.

---

## 🏗️ Architecture

```mermaid
graph TD
    A[Claude / AI Client] -->|MCP Protocol| B[LiveDocs MCP Server]

    B --> C{Cache Hit?}
    C -->|Yes - 24h TTL| D[Return Cached Result]
    C -->|No| E[Serper Google Search API]

    E --> F[Top 5 Doc URLs]
    F --> G[Concurrent HTTP Fetch]
    G --> H[trafilatura HTML → Text]
    H --> I[Code Block Extraction]
    I --> J[Cache + Return]

    B --> K[list_libraries]
    B --> L[cache_stats]

    subgraph Tools
        B --> M[get_docs]
        B --> N[search_docs_multi]
        B --> O[get_code_examples]
    end
```

---

## 🔑 API Keys

| Key              | Purpose                   | Free Tier               | Get It                                       |
| ---------------- | ------------------------- | ----------------------- | -------------------------------------------- |
| `SERPER_API_KEY` | Google search via Serper  | ✅ 2,500 searches/month | [serper.dev](https://serper.dev)             |
| `GROQ_API_KEY`   | LLM answers in CLI client | ✅ Generous free tier   | [console.groq.com](https://console.groq.com) |

---

## 💡 Example Prompts

Once connected in Claude, try:

```
"Search the LangChain docs for how to use structured output with tool calling"

"Compare how LangChain and LlamaIndex implement document chunking"

"Get me a code example for streaming with the OpenAI Assistants API"

"What changed in CrewAI v0.7?"

"List all supported vector database libraries"
```

---

## 🗂️ Project Structure

```
live-docs-mcp/
├── mcp_server.py      # 🚀 Production MCP server (5 tools)
├── mcp_client.py      # 🖥️ Interactive CLI client
├── libraries.py       # 📋 Registry of 45+ libraries
├── cache.py           # ⚡ TTL in-memory cache
├── utils.py           # 🔧 HTML extractor + code parser
├── render.yaml        # 🌐 One-click Render deployment
├── pyproject.toml     # 📦 Dependencies (uv)
├── .env.example       # 🔑 Environment variable template
└── README.md
```

---

## 🤝 Contributing

Want to add a library? Edit `libraries.py` — it takes 5 lines:

```python
"your_library": {
    "site": "docs.your-library.com",
    "description": "Short description of the library",
    "category": "llm_frameworks",   # see existing categories
    "aliases": ["yl", "yourlib"],   # optional short names
},
```

Then open a PR. ✨

---

## 📄 License

MIT — free to use, modify, and deploy.

---

<p align="center">Built with ❤️ for AI engineers who are tired of stale docs.</p>