Otter Bridge

by typangaa

173 downloads

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About

OtterBridge is a lightweight, flexible server for connecting applications to various Large Language Model providers. Following the principles of simplicity and composability outlined in Anthropic's guide to building effective agents, OtterBridge provides a clean interface to LLMs

Details

Author: typangaa
Downloads: 173
Categories: Developer Tools

- Provider-agnostic design (currently Ollama, ChatGPT and Claude planned)
- Simple, composable architecture inspired by effective agent patterns
- Lightweight server built with FastMCP
- Easy model management and retrieval of model capabilities
- Configurable via environment variables (OLLAMA_BASE_URL, DEFAULT_MODEL)

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Otter Bridge

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

From the repository

Install prerequisites (Ollama and uv), clone the repository, install dependencies with uv add -r requirements.txt, copy .env.example to .env, and configure environment variables. Start the server manually with uv run server.py or automatically via MCP clients like Claude Desktop (add the server to the desktop configuration). Two tools are available: chat (send messages to LLMs) and list_models (retrieve available model information).

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "otter bridge": {
            "otterbridge": {
                "command": "uv",
                "args": [
                    "run",
                    "server.py"
                ]
            }
        }
    }
}

McpServers

{
    "otterbridge": {
        "command": "uv",
        "args": [
            "run",
            "server.py"
        ]
    }
}

otterbridge

OtterBridge is a lightweight, mcp server for connecting applications to various Large Language Model providers.

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