Connect Mattermost with MCP servers for command execution and tool management via Python client
The Ollama-MCP Server is a versatile and universal adapter designed to facilitate seamless integration between various AI applications like Claude Desktop, Continue, Cursor, and other tools through the Model Context Protocol (MCP). This server acts as a bridge, enabling these AI applications to connect with specific data sources and tools through a standardized protocol. By leveraging MCP, it offers enhanced flexibility and compatibility, allowing developers to integrate a wide range of AI applications into their workflows efficiently.
The Ollama-MCP Server integrates deeply with the Model Context Protocol (MCP), providing core features that enhance its functionality for AI application integration. This server supports the following MCP capabilities:
These features are pivotal in making the Ollama-MCP Server a robust choice for developers working with diverse AI applications. The server integrates these capabilities through a structured protocol flow, as illustrated below.
The Model Context Protocol (MCP) architecture ensures that the communication between the Ollama-MCP Server and other AI clients is efficient and secure. Below is a detailed explanation of how MCP is implemented in this server:
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Data Source/Tool]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
graph TD
A[Data Source] -- Data --> B[MCP Protocol]
B -- Requests/Responses --> C[MCP Client]
C -- Control/Feedback --> D[Tool Execution]
This architecture ensures that the data exchanged between the AI application and the Ollama-MCP Server is structured and well-defined, promoting a smooth integration experience.
To get started with the installation of the Ollama-MCP Server, follow these steps:
Create a Virtual Environment
uv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# On fish shell - source .venv/bin/activate.fish
Install Required Packages
uv sync # Installs all dependencies
Set Up Configuration
Create a .env
file in your project directory with the following content:
MATTERMOST_URL=http://localhost:8065
MATTERMOST_TOKEN=your-bot-token
MATTERMOST_SCHEME=http
MATTERMOST_PORT=8065
MATTERMOST_TEAM_NAME=your-team-name
MATTERMOST_CHANNEL_NAME=town-square
MCP_SERVER_TYPE=stdio
MCP_COMMAND=python
MCP_ARGS=mcp_server.py
LOG_LEVEL=INFO
Configure MCP Servers
Create or modify the mcp-servers.json
file in the src/mattermost_mcp_client
directory:
{
"mcpServers": {
"ollama-mcp-server":{
"command": "python",
"args": ["ollama-mcp-server/src/ollama_mcp_server/main.py"],
"type": "stdio"
}
}
}
Run the Integration
python src/mattermost_mcp_client/main.py
The Ollama-MCP Server offers several key use cases that enhance AI workflows, making it a valuable tool for developers working with diverse applications:
Imagine an AI application that needs to fetch real-time data from various sources and transform it into actionable insights. By leveraging the Ollama-MCP Server, you can easily configure this process where the MCP client requests the necessary data, which is then fetched by the server and transformed according to predefined rules.
Developers working with AI applications that rely heavily on prompts for text generation tasks can benefit significantly from this integration. The Ollama-MCP Server allows these applications to generate dynamic content based on user inputs, ensuring a more interactive and personalized experience.
The Ollama-MCP Server integrates seamlessly with other MCP clients like Claude Desktop, Continue, and Cursor. Here’s how each of these clients can utilize the server:
For a complete list of supported MCP clients, refer to the provided compatibility matrix below.
The following compatibility matrix outlines the current state of the Ollama-MCP Server in terms of client compatibility:
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
This matrix helps developers understand the level of support and functionality available for different MCP clients.
To ensure optimal performance and security, developers can configure various aspects of the Ollama-MCP Server:
{
"mcpServers": {
"[server-name]":{
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-[name]"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
Here are some frequently asked questions regarding the Ollama-MCP Server:
Q: Can I integrate multiple AI applications with a single Ollama-MCP Server? A: Yes, you can configure multiple MCP clients and use this server to manage their interactions effectively.
Q: How does the Ollama-MCP Server handle data privacy during communication? A: The server supports end-to-end encryption for secure data transmission between AI applications and backend services.
Q: Is it possible to integrate file uploads through the MCP Protocol in this server? A: While the current implementation focuses on command execution, future updates may include support for file uploads and other advanced features.
Q: Can I customize the tool management logic within the Ollama-MCP Server? A: Yes, developers can customize the tool management processes through the server configuration options provided by the protocol.
Q: How do I troubleshoot connection issues between AI applications and the MCP client? A: Common troubleshooting steps include verifying the Mattermost URL, checking bot token validity, and ensuring the MCP server is running properly.
Contribution to the Ollama-MCP Server is highly encouraged for developers looking to enhance its features and capabilities. To contribute, follow these guidelines:
After making significant contributions, you can create a pull request for the main repository.
To ensure high-quality documentation:
This documentation positions the Ollama-MCP Server as a valuable tool for developers looking to integrate multiple AI applications through a standardized protocol, enhancing efficiency and flexibility in their workflows.
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