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# MCP Server Project

This repository contains an implementation of a Model Context Protocol (MCP) server. This project demonstrates how to build and run a functional MCP server that can integrate with LLM clients like Claude Desktop.

## Key Features

This MCP server provides a suite of tools focused on information retrieval and vector database management, primarily leveraging LangChain and ChromaDB:

*   **Targeted Documentation Search**:
    *   Quickly search the official documentation for popular AI/ML libraries:
        *   Langchain
        *   OpenAI
        *   LlamaIndex
    *   Retrieves relevant text snippets directly from the documentation sites.

*   **ChromaDB Vector Database Integration**:
    *   **Setup**: Create and initialize ChromaDB vector stores with your own text data and optional metadata.
    *   **Persistence**: Option to persist databases to disk for later use or use in-memory stores.
    *   **Querying**: Perform semantic searches on your ChromaDB instances to find relevant documents based on query similarity.
    *   **Demonstration**: A built-in demo tool to showcase the setup and query capabilities with sample data.

*   **Powered by LangChain**:
    *   Utilizes LangChain for core functionalities like document handling, embedding management (using OpenAI Embeddings by default), and vector store interactions.

## System Requirements

- Python 3.11 or higher (as specified in `pyproject.toml`)
- `uv` package manager
- Dependencies listed in `pyproject.toml` (e.g., `mcp[cli]`, `httpx`, `langchain`)

## Getting Started

### 1. Install `uv` Package Manager

If you don't have `uv` installed, you can install it using:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
Restart your terminal after installation.

### 2. Project Setup

Clone this repository (if you haven't already) and navigate into the project directory:
```bash
# cd /path/to/your/mcp-server
```

Create a virtual environment and install dependencies:
```bash
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -r requirements.txt # Or use uv pip install -e . if setup.py or pyproject.toml is configured for editable install
# Based on your pyproject.toml, you might also directly use:
# uv add beautifulsoup4 httpx "mcp[cli]" langchain langchain-community langchain-core chromadb
# Or more simply if pyproject.toml is complete:
# uv sync
```
*(Note: Ensure your `pyproject.toml` is complete or you have a `requirements.txt` for `uv pip install -r requirements.txt`. `uv sync` is often preferred if `pyproject.toml` defines all dependencies.)*

### 3. Running the Server

To start the MCP server, run:
```bash
uv run main.py
```
The server will start and be ready to accept connections.

## Connecting to Claude Desktop

To connect this MCP server to Claude Desktop:

1.  Ensure Claude Desktop is installed.
2.  Edit the Claude Desktop configuration file located at `~/Library/Application Support/Claude/claude_desktop_config.json` (on macOS).
3.  Add or update the `mcpServers` section:

    ```json
    {
        "mcpServers": {
            "mcp-server": { // You can choose any name
                "command": "/full/path/to/your/.venv/bin/uv", // Use absolute path to uv in your venv
                "args": [
                    "run",
                    "main.py"
                ],
                "dir": "/full/path/to/your/mcp-server" // Absolute path to this project directory
            }
        }
    }
    ```
    **Important:** Replace `/full/path/to/your/...` with the correct absolute paths on your system. Using the `uv` from your project's virtual environment is recommended.

4.  Restart Claude Desktop.

## Acknowledgements

This project is largely based on the `mcp-server-example` generously provided by Alejandro AO. We have adapted and utilized significant portions of his original work to build this server. We extend our sincere gratitude to Alejandro for his excellent example and for making his code available to the community.

You can find Alejandro AO's original repository here: [https://github.com/alejandro-ao/mcp-server-example](https://github.com/alejandro-ao/mcp-server-example).

## License

This project is licensed under the MIT License. See the `LICENSE` file for more details (if one exists).

TDQS

A3.9/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: get_docs searches documentation, setup_chroma_db initializes a vector database, query_chroma_db retrieves results, and chroma_db_demo runs a combined demonstration. No two tools overlap in a way that would cause misselection.

Naming Consistency4/5

Three tools follow a clear verb_noun pattern (get_docs, setup_chroma_db, query_chroma_db), while chroma_db_demo deviates to a noun_noun style. However, all names use snake_case and are predictable and readable.

Tool Count5/5

With four tools focused on docs search and ChromaDB operations, the count is well-scoped and each tool earns its place. It is neither too thin nor overloaded for the apparent purpose.

Completeness4/5

The core workflows are covered: search docs, set up a vector DB, and query it. Minor gaps exist—no update/delete for vectors and docs search limited to three libraries—but agents can work around these limitations.

Maintenance

ActivityInactive
ResponsivenessNo issues