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Ollama-MCP Bridge WebUI

Ollama-MCP Bridge WebUI

Local
github.com/Rkm1999AI & Agents5Updated 82w ago

About Ollama-MCP Bridge WebUI

Ollama-MCP Bridge WebUI connects local Ollama models to MCP servers through a web interface, for users running AI assistants on their own hardware. It supports multiple MCP servers and routes queries to tools for filesystem operations, web search, and reasoning.

Key features

  1. 01Connect multiple MCP servers
  2. 02Select tools based on queries
  3. 03Provide a web interface
  4. 04Offer filesystem, web search, and reasoning tools
  5. 05Load server and model settings from configuration

Use cases

  1. 01Let local Ollama models use MCP tools
  2. 02Work with files or search the web through the UI

MCP support

The bridge reads MCP server definitions from its configuration and makes their tools available to local Ollama models.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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:

  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:

# 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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.