Ollama-MCP Bridge WebUI

A TypeScript implementation that connects local LLMs (via Ollama) to Model Context Protocol (MCP) servers with a web interface. This bridge allows open-source models to use the same tools and capabilities as Claude, enabling powerful local AI assistants that run entirely on your own hardware.

Features

- Multi-MCP Integration: Connect multiple MCP servers simultaneously
- Tool Detection: Automatically identifies which tool to use based on queries
- Web Interface: Clean UI with collapsible tool descriptions
- Comprehensive Toolset: Filesystem, web search, and reasoning capabilities

Setup

Automatic Installation

The easiest way to set up the bridge is to use the included installation script:

./install.bat

This script will:
1. Check for and install Node.js if needed
2. Check for and install Ollama if needed
3. Install all dependencies
4. Create the workspace directory (../workspace)
5. Set up initial configuration
6. Build the TypeScript project
7. Download the Qwen model for Ollama

After running the script, you only need to:
1. Add your API keys to the .env file (the $VARIABLE_NAME references in the config will be replaced with actual values)

Manual Setup

If you prefer to set up manually:

1. Install Ollama from ollama.com/download
2. Pull the Qwen model: ollama pull qwen2.5-coder:7b-instruct-q4_K_M
3. Install dependencies: npm install
4. Create a workspace directory: mkdir ../workspace
5. Configure API keys in .env
6. Build the project: npm run build

Configuration

The bridge is configured through two main files:

1. bridge_config.json

This file defines MCP servers, LLM settings, and system prompt. Environment variables are referenced with $VARIABLE_NAME syntax.

Example:

{

  "mcpServers": {

    "filesystem": {

      "command": "node",

      "args": [

        "To/Your/Directory/Ollama-MCP-Bridge-WebUI/node_modules/@modelcontextprotocol/server-filesystem/dist/index.js",

        "To/Your/Directory/Ollama-MCP-Bridge-WebUI/../workspace"

      ],

      "allowedDirectory": "To/Your/Directory/Ollama-MCP-Bridge-WebUI/../workspace"

    },

    "brave-search": {

      "command": "node",

      "args": [

        "To/Your/Directory/Ollama-MCP-Bridge-WebUI/node_modules/@modelcontextprotocol/server-brave-search/dist/index.js"

      ],

      "env": {

        "BRAVE_API_KEY": "$BRAVE_API_KEY"

      }

    },

    "sequential-thinking": {

      "command": "node",

      "args": [

        "To/Your/Directory/Ollama-MCP-Bridge-WebUI/node_modules/@modelcontextprotocol/server-sequential-thinking/dist/index.js"

      ]

    }

  },

  "llm": {

    "model": "qwen2.5-coder:7b-instruct-q4_K_M",

    "baseUrl": "http://localhost:11434",

    "apiKey": "ollama",

    "temperature": 0.7,

    "maxTokens": 8000

  },

  "systemPrompt": "You are a helpful assistant that can use various tools to help answer questions. You have access to three main tool groups: 1) Filesystem operations - for working with files and directories, 2) Brave search - for finding information on the web, 3) Sequential thinking for complex problem-solving. When a user asks a question that requires external information, real-time data, or file manipulation, you should use a tool rather than guessing or using only your pre-trained knowledge."

}

2. .env file

This file stores sensitive information like API keys:

```