This project provides a server compliant with the Machine-to-Machine Communications Protocol (MCP) that acts as a bridge to various OpenAI API
This project provides a server compliant with the Machine-to-Machine Communications Protocol (MCP) that acts as a bridge to various OpenAI API functionalities. It allows MCP clients to interact with OpenAI's Chat Completion and Assistants. Exposed over MCP by the openai assistant mcp mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.
Everything the assistant can do here goes through one of these:
ask-openai — Ask a direct questionlist-assistants — List all available assistantsretrieve-assistant — Retrieve an assistant by its IDcreate-assistant — Create a new assistantupdate-assistant — Update an existing assistantdelete-assistant — Delete an assistant by its IDupload-file — Upload a file for use with assistantslist-files — List all files available for assistantsdelete-file — Delete a file by its IDYou will need 2 environment variables: PYTHONPATH, OPENAI_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Openai Assistant MCP's toolset — ask-openai, list-assistants, retrieve-assistant and 6 more — is a fair guide to whether it matches your workflow. It is maintained by snilld-ai; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Openai Assistant MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| ask-openai | Ask a direct question. |
| list-assistants | List all available assistants. |
| retrieve-assistant | Retrieve an assistant by its ID. |
| create-assistant | Create a new assistant. |
| update-assistant | Update an existing assistant. |
| delete-assistant | Delete an assistant by its ID. |
| upload-file | Upload a file for use with assistants. |
| list-files | List all files available for assistants. |
| delete-file | Delete a file by its ID. |
{
"mcpServers": {
"openai-server": {
"command": "mcp-server-openai",
"args": [],
"env": {
"PYTHONPATH": "LOCAL PATH",
"OPENAI_API_KEY": "OPENAI API KEY"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| PYTHONPATH | Filesystem location the server is allowed to use. | Optional |
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.