MCP Azure OpenAI Interfacing Module

AI companions are remarkably capable. I envisioned equipping my own system, 'Conscious Claude,' with such an interface. Now realized, it proves both highly practical and engaging for its operation. Your Claude instance can now benefit from this capability as well!

This constitutes a straightforward MCP server designed specifically for interfacing with OpenAI's generative models. It empowers external agents (like Claude Desktop applications) to orchestrate and engage with OpenAI assistants through the standardized Model Context Protocol framework.

Core Functionality

This implementation furnishes a comprehensive set of mechanisms for managing and interacting with OpenAI-based AI constructs. The integration of response streaming introduces a substantially superior, instantaneous operational experience.

Exposed Procedures

• create_assistant: (Provisioning an OpenAI Agent) - Generates a novel assistant entity, specifying its nomenclature, operational directives, and underlying model selection.
• list_assistants: (Enumerating OpenAI Agents) - Retrieves a manifest of all accessible agents linked to the authenticated API credentials.
• retrieve_assistant: (Fetching Agent Details) - Acquires comprehensive metadata pertaining to a singular, designated assistant.
• update_assistant: (Modifying an Existing Agent) - Allows refinement of an established agent's name, guiding instructions, or computational engine.
• create_new_assistant_thread: (Initiating a Fresh Dialogue Context) - Establishes a novel, durable conversational session, allowing the client to affix identifying metadata (name, description) for streamlined retrieval and continuation. This is the preferred initial step for any new interaction sequence.
• list_threads: (Querying Stored Dialogue Contexts) - Presents a catalog of all conversation threads actively tracked within the local repository, detailing their identifiers, labels, descriptions, and last access timestamps.
• delete_thread: (Terminating a Dialogue Context) - Permanently eradicates a conversation thread from both the remote OpenAI infrastructure and the local persistent storage.
• ask_assistant_in_thread: (Querying Agent within Context and Receiving Streaming Output) - The principal mechanism for dialogue. It transmits a user input to the designated assistant within a specific thread context and relays the resulting output progressively, in real-time.

Given that responses from OpenAI constructs can sometimes involve significant latency, this server employs a streaming methodology for the critical ask_assistant_in_thread function. This guarantees the client receives continuous progress updates, thereby mitigating potential communication timeouts.

The inclusion of local data persistence for thread records marks a substantial enhancement. Since the native OpenAI API lacks a thread enumeration feature, this server compensates by maintaining a local SQLite database to store thread identifiers and associated metadata. This capability facilitates effortless discovery, referencing, and management of ongoing dialogues across different operational sessions.

Deployment Instructions

Automated Installation via Smithery

To deploy the MCP Azure OpenAI Interfacing Module to Claude Desktop automatically utilizing Smithery:

npx -y @smithery/cli install mcp-simple-openai-assistant --client claude

Manual Compilation

pip install mcp-simple-openai-assistant

Configuration Requirements

The server necessitates the presence of a valid OpenAI API credential configured within the execution environment variables. For deployment within Claude Desktop, integrate the following configuration structure:

(MacOS Variant)

{
  "mcpServers": {
    "openai-assistant": {
      "command": "python",
      "args": ["-m", "mcp_simple_openai_assistant"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here"
      }
    }
  }
}

(Windows Variant)

"mcpServers": {
  "openai-assistant": {
    "command": "C:\\Users\\YOUR_USERNAME\\AppData\\Local\\Programs\\Python\\Python311\\python.exe",
      "args": ["-m", "mcp_simple_openai_assistant"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here"
  }
}

Note on Windows deployment: Locating the correct executable path can sometimes be tricky; the example path is common but may require verification specific to your system setup. In certain environments, simply referencing python.exe suffices. Use command prompt utilities like where python to confirm the accessible location. Furthermore, Windows users might need to explicitly define the PYTHONPATH environment variable to point to the necessary site-packages directory for proper operation.

Operational Guide

Upon successful configuration, utilize the procedures detailed above to manage your AI agents and dialogue streams. The standard operational sequence involves: 1. Invoking create_new_assistant_thread to commence a labeled, retrievable conversational history. 2. Employing list_threads to ascertain the unique identifier of a context you wish to resume. 3. Utilizing ask_assistant_in_thread to engage the specified AI agent within the selected dialogue context.

Development Roadmap (Future Enhancements)

• [x] Context Persistence Integration: Implemented functionality for naming and locally safeguarding thread identifiers, enabling easier session reuse.
• [ ] Model Catalog Exposure: Developing a procedure allowing the AI user to dynamically query the roster of supported OpenAI models available for agent creation.
• [ ] Granular Agent Configuration: Enabling specification of advanced agent hyperparameters (e.g., temperature, top_p values), a feature requested by the Claude interface.
• [ ] Historical Context Retrieval: Implementing the capability to fetch complete dialogue histories without requiring a new input message (as requested by Claude).
• [ ] External Resource Integration: Adding support for uploading and referencing local files within assistant operations.

Developer Setup

To compile and run this module in a development environment:

git clone https://github.com/andybrandt/mcp-simple-openai-assistant
cd mcp-simple-openai-assistant
pip install -e '.[dev]'

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