Ollama-MCP Bridge WebUI
A web interface connecting local Ollama LLMs to Model Context Protocol (MCP) servers. Enables open-source models to use file operations, web search, and reasoning tools similar to commercial AI assistants - all running privately on your own hardware.
Rkm1999
README
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:
- Check for and install Node.js if needed
- Check for and install Ollama if needed
- Install all dependencies
- Create the workspace directory (../workspace)
- Set up initial configuration
- Build the TypeScript project
- Download the Qwen model for Ollama
After running the script, you only need to:
- 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:
- Install Ollama from ollama.com/download
- Pull the Qwen model:
ollama pull qwen2.5-coder:7b-instruct-q4_K_M
- Install dependencies:
npm install
- Create a workspace directory:
mkdir ../workspace
- Configure API keys in
.env
- 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:
# Brave Search API key
BRAVE_API_KEY=your_brave_key_here
The bridge will automatically replace $BRAVE_API_KEY
in the configuration with the actual value from your .env
file.
Usage
Starting the Bridge
Simply run:
./start.bat
This will start the bridge with the web interface.
Web Interface
Open http://localhost:8080 (or the port shown in the console) in your browser to access the web interface.
License
MIT License - See LICENSE file for details
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