MCP server for AI dialogue using various LLM models via AceDataCloud
MCP server for AI dialogue using various LLM models via AceDataCloud. That is what the mcp mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
A Model Context Protocol (MCP) server for AI dialogue via the AceDataCloud platform. Supports a wide range of models including GPT-4/5, o-series, DeepSeek, Grok, and GLM.
The server publishes 6 tools. What each one is for:
aichat_create_conversation — Create an AI conversation with any supported modelaichat_create_conversation_v2 — Create/manage conversations via /aichat2/conversationsaichat_list_models — List all available AI modelsaichat_get_usage_guide — Get API usage guideOpenAI — The OpenAI tool exposed by this serverDeepSeek — The DeepSeek tool exposed by this serverConfiguration is passed through the environment: ACEDATACLOUD_API_TOKEN. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
The server ships on PyPI as mcp-aichat, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
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. MCP's toolset — aichat_create_conversation, aichat_create_conversation_v2, aichat_list_models and 3 more — is a fair guide to whether it matches your workflow. It is maintained by AceDataCloud; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| aichat_create_conversation | Create an AI conversation with any supported model |
| aichat_create_conversation_v2 | Create/manage conversations via /aichat2/conversations |
| aichat_list_models | List all available AI models |
| aichat_get_usage_guide | Get API usage guide |
| OpenAI | The OpenAI tool exposed by this server. |
| DeepSeek | The DeepSeek tool exposed by this server. |
{
"mcpServers": {
"aichat": {
"command": "uvx",
"args": ["mcp-aichat"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| ACEDATACLOUD_API_TOKEN | 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.