Mcp Aichat

io.github.AceDataCloud由 GitHub 帳號 AceDataCloud 發布v2026.11.1.3更新於 Nov 3, 2026

MCP server for AI dialogue using various LLM models via AceDataCloud

已驗證Streamable HTTP可網頁執行溝通與協作AI 與機器學習

概覽

AI 產生的概覽

AceDataCloud 的 AiChat MCP 伺服器讓助理向多種託管大型語言模型提問,並支援多輪對話。

可以做什麼
  • 向指定模型提問並取得生成的回答,可用對話 ID 接續多輪對話
  • 使用 v2 對話端點,支援代理式多輪迭代與可選的伺服器端對話狀態
  • 依供應商列出可用模型,例如 OpenAI、DeepSeek、xAI、智譜、Gemini 與 Kimi
  • 取得使用指南,了解參數、範例與最佳實務
適用情境
適合想透過單一 MCP 連線存取多個模型系列(GPT、o 系列、DeepSeek、Grok、GLM、Gemini、Kimi),而不必分別串接各家服務;也適合需要伺服器端對話狀態與外部參考資料來產生具情境脈絡回答的情況。
執行需求
可使用託管端點並以 OAuth 登入 AceDataCloud 帳號,或以 Bearer 標頭傳送 AceDataCloud API 權杖;也可在本機執行 PyPI 套件 mcp-aichat(uvx 或 pip),並設定 ACEDATACLOUD_API_TOKEN。始終需要能連線至 AceDataCloud API 的網路。
安裝前請注意
託管服務可能依用量計費,每次模型呼叫依實際用量收費,使用前請確認價格與帳戶餘額。API 權杖屬於機密:應存放在憑證儲存區或環境變數中,不要寫入提示詞、共用設定或提交紀錄,也不要同時設定 OAuth 登入與固定 Authorization 標頭。請求與提示詞會傳送給第三方 AceDataCloud,且工具已列出或任務已提交並不代表執行成功。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Mcp Aichat,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.AceDataCloud%2Fmcp-aichat/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "aichat": {
      "type": "http",
      "url": "https://aichat.mcp.acedata.cloud/mcp"
    }
  }
}

README

MCP AiChat Server

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.

Ace Data Cloud in goose

Named provider preset and upstream acceptance status. This independently installed preset is not an official built-in provider.

Features

  • Multi-model support: GPT-4.1, GPT-4o, GPT-5, o1, o3, o4-mini, DeepSeek, Grok, GLM, and more
  • Multi-turn conversations: Continue conversations using conversation IDs
  • Stateful mode: Optional server-side conversation state management
  • Reference sources: Include external references for context-aware responses

Connect: hosted OAuth, API token, or local stdio

The hosted endpoint is https://aichat.mcp.acedata.cloud/mcp. Choose one route for the MCP client:

RouteWhen to use itCredential setup
Hosted OAuthThe client supports remote MCP OAuthAdd only the URL, then sign in to AceDataCloud and approve access. No token needs to be pasted into client configuration.
Hosted API tokenThe client cannot finish OAuth, or you need an explicit integration credentialSend an AceDataCloud API token in the Authorization: Bearer … header. Keep it in a local secret store or environment variable.
Local stdioThe client runs a local MCP processInstall mcp-aichat and pass ACEDATACLOUD_API_TOKEN to that process. It still calls the AceDataCloud API.

The hosted service advertises OAuth metadata and Dynamic Client Registration (DCR). DCR registers the client application; it is not an API key. OAuth signs you in and the client sends the resulting Bearer token; it may reuse or create an API credential for the account. Browser sign-in still requires an AceDataCloud account. The hosted service can be metered: review current service documentation and displayed pricing before a real operation. Do not configure both an OAuth login and a fixed Authorization header for the same server.

Hosted OAuth examples

  • Claude and Claude Desktop chat: Add a remote custom connector in Customize → Connectors → Add custom connector, enter https://aichat.mcp.acedata.cloud/mcp, select sign-in, and choose Register automatically if Claude asks how to register its OAuth client. Complete consent. Claude Desktop's local claude_desktop_config.json is a separate setup. Claude connector guide.
  • Claude Code: claude mcp add --transport http --scope user aichat https://aichat.mcp.acedata.cloud/mcp, then claude mcp login aichat. Check /mcp. Claude Code MCP guide.
  • Cursor: Add a remote server with only https://aichat.mcp.acedata.cloud/mcp. For a project, merge the entry below into <project>/.cursor/mcp.json; for personal use, use ~/.cursor/mcp.json. Cursor MCP guide.
  • VS Code / Copilot: Run MCP: Add Server, select HTTP, enter https://aichat.mcp.acedata.cloud/mcp, then finish the browser sign-in. New portable workspace configs use <project>/.mcp.json; the VS Code-specific format below uses <project>/.vscode/mcp.json or the user profile. Check MCP: List Servers. VS Code MCP setup.
  • Codex: codex mcp add aichat --url https://aichat.mcp.acedata.cloud/mcp, then codex mcp login aichat. Its user settings are in ~/.codex/config.toml. Official Codex MCP guide.

Cursor project config (OAuth):

json
{  "mcpServers": {    "aichat": {"url": "https://aichat.mcp.acedata.cloud/mcp"}  }}

VS Code-specific workspace config (OAuth):

json
{  "servers": {    "aichat": {"type": "http", "url": "https://aichat.mcp.acedata.cloud/mcp"}  }}

Hosted API token

  1. Open Ace Data Cloud → Applications. Sign in, or register an account first.
  2. Find General application. If it has not been created, choose Initialize General Application. A general key can use the services available to your account; a dedicated application's key is limited to its service. Check the required service/model access and current pricing.
  3. Copy the API Key from the application card, or open Keys / Manage Keys → Create to create a separate key for this integration. Give it a recognizable name so you can revoke or rotate it independently.
  4. When creating a key, review Expiration Time, Set Usage Limitation, and Allowed APIs. Enable only the restrictions you need, allow the operations you will call, then click Create and copy the token from the key list. Task lookup does not grant permission to submit a generation. Confirm the application's balance can cover your first request; any trial allowance is whatever your account currently displays.
  5. Copy only the token value, without quotation marks, spaces, or Bearer . An API Key / API Token field expects this raw value; only a manually configured HTTP Authorization header needs the Bearer prefix. A platform-... account-management token cannot replace a generation API key.

[Copy an application API key or open Manage Keys]

[Create a separately named key with optional restrictions]

Save the key in the client's credential store or the environment variable shown below. Never put it in a prompt, shared workflow, screenshot, or Git commit. If authentication fails, check the full copied value, application/service access, expiration, usage limit, and balance before creating another key.

A fixed Bearer header bypasses OAuth. If the header is invalid, remove it before trying browser sign-in; keep the saved credential private.

For Claude Code, the shell expands the token when you add the server; treat the saved user MCP config as a secret:

bash
export ACEDATACLOUD_API_TOKEN='YOUR_API_TOKEN'claude mcp add --transport http --scope user aichat https://aichat.mcp.acedata.cloud/mcp \  --header "Authorization: Bearer $ACEDATACLOUD_API_TOKEN"

For a Claude Code project config, put a variable reference in <project>/.mcp.json and set that variable in the environment that launches Claude Code:

json
{  "mcpServers": {    "aichat": {      "type": "http",      "url": "https://aichat.mcp.acedata.cloud/mcp",      "headers": {"Authorization": "Bearer ${ACEDATACLOUD_API_TOKEN}"}    }  }}

Cursor uses a different environment-variable syntax in ~/.cursor/mcp.json or an uncommitted project config:

json
{  "mcpServers": {    "aichat": {      "url": "https://aichat.mcp.acedata.cloud/mcp",      "headers": {"Authorization": "Bearer ${env:ACEDATACLOUD_API_TOKEN}"}    }  }}

In VS Code, run MCP: Open User Configuration and merge this server plus its masked input; ${input:...} is for VS Code's user/workspace format and is not portable to the Agent Host .mcp.json format:

json
{  "inputs": [    {"id": "acedata-aichat-token", "type": "promptString", "description": "AceDataCloud API token", "password": true}  ],  "servers": {    "aichat": {      "type": "http",      "url": "https://aichat.mcp.acedata.cloud/mcp",      "headers": {"Authorization": "Bearer ${input:acedata-aichat-token}"}    }  }}

For Cline, use its MCP configuration UI or CLI file ~/.cline/data/settings/cline_mcp_settings.json; its remote transport value is streamableHttp. For JetBrains AI Assistant, add a remote URL from Settings → Tools → AI Assistant → Model Context Protocol (MCP). For Zed, use a context_servers entry with the URL only for OAuth or add a local Bearer header. These clients have different configuration schemas; follow their current UI rather than copying another client's JSON. Cline · JetBrains · Zed.

Local stdio

Install the package and give the local process an API token:

bash
python -m pip install mcp-aichatexport ACEDATACLOUD_API_TOKEN='YOUR_API_TOKEN'mcp-aichat

For Claude Desktop local MCP, merge this entry into the file opened by its developer settings (~/Library/Application Support/Claude/claude_desktop_config.json on macOS). uvx requires uv on PATH:

json
{  "mcpServers": {    "aichat": {      "command": "uvx",      "args": ["mcp-aichat"],      "env": {"ACEDATACLOUD_API_TOKEN": "YOUR_API_TOKEN"}    }  }}

Keep this user-level file private. Self-hosted HTTP uses mcp-aichat --transport http --port 8000; expose it only with suitable network and TLS controls. Local execution still calls the AceDataCloud API.

Check before using the service

  1. https://aichat.mcp.acedata.cloud/health returning {"status":"ok"} checks endpoint reachability only.
  2. Confirm that the MCP client loads tools. aichat_list_models is a reference tool; it does not verify downstream API access or balance.
  3. If you need a full API check, call aichat_create_conversation with your own valid input after reviewing current service documentation and displayed pricing.

For 401, check which auth route the client used and whether the token or OAuth session is valid. A 403 may mean an account permission or content moderation failure; read the returned error. Insufficient balance and downstream service failures need their own diagnosis. A listed tool or submitted task does not prove a successful result.

Available Tools

ToolDescription
aichat_create_conversationCreate an AI conversation with any supported model
aichat_create_conversation_v2Create/manage conversations via /aichat2/conversations
aichat_list_modelsList all available AI models
aichat_get_usage_guideGet API usage guide

AiChat v2 agent iterations

aichat_create_conversation_v2 accepts max_turns from 1 to 500. Omit it to use the Backend default of 500. This limits agent iterations for one request, not conversation-history length; max_turns=1 prevents tool calls. Each model call is billed by actual usage, and execution may end earlier due to timeouts, authorization or other execution conditions.

Supported Models

OpenAI

  • GPT-5.6 Sol Fast: gpt-5.6-sol-fast, supported by both aichat_create_conversation and aichat_create_conversation_v2. Existing defaults are unchanged.
  • GPT-5 series: gpt-5.5, gpt-5.4, gpt-5.2, gpt-5.1, gpt-5, gpt-5-mini, gpt-5-nano
  • GPT-4.1 series: gpt-4.1, gpt-4.1-mini, gpt-4.1-nano
  • GPT-4o series: gpt-4o, gpt-4o-mini, gpt-4o-all, gpt-4o-image
  • GPT-4 series: gpt-4, gpt-4-turbo, gpt-4-vision-preview
  • o-series: o1, o1-mini, o1-pro, o3, o3-mini, o3-pro, o4-mini

DeepSeek

  • deepseek-r1, deepseek-r1-0528, deepseek-v3, deepseek-v3-250324, deepseek-v4-flash, deepseek-v4-pro

xAI

  • grok-3

Zhipu AI

  • glm-5.1, glm-4.7, glm-4.6, glm-3-turbo

Google Gemini

gemini-3.8-flash is available through both conversation tools. Use aichat_create_conversation_v2 with model="gemini-4-argon" for Gemini 4 Argon. It is not available through the v1 tool; the default remains gpt-4.1.

json
{"model":"gemini-4-argon","question":"Review this code and identify its key risks."}

Pass these arguments to aichat_create_conversation_v2. This uses /aichat2/conversations, not native Gemini Generate Content or Google Interactions. The MCP tool does not expose max_tokens, thinking-level or explicit-cache controls; native endpoint capabilities do not imply those controls are available through this conversation wrapper.

Kimi (AiChat v2 only)

Use aichat_create_conversation_v2 with model="kimi-k3.1-pro" to use Kimi K3.1 Pro. kimi-k3 and existing v2 Kimi aliases remain supported; the default model is still gpt-4.1. These models are not available through the v1 tool.

json
{"model":"kimi-k3.1-pro","question":"Review this code and identify its key risks."}

Pass these arguments to aichat_create_conversation_v2. The tool calls /aichat2/conversations, not /kimi/chat/completions, and does not expose the latter endpoint's reasoning_effort control.

Documentation

Documentation

License

MIT

MiMo integration status

The typed inputs include mimo-v2.6-pro, mimo-v2.6-flash and the v2 mimo group. Check the current model catalog, service status and account access before calling them. Initial scope is text, reasoning and function tools; built-in web search and multimodal inputs are not enabled.

來源:README.md,提交 248329f

工具

4

aichat_create_conversation

Create an AI conversation using the AiChat API. Sends a question to the specified AI model and returns the generated answer. Supports a wide range of models including GPT-4, GPT-5, o-series, DeepSeek, Grok, and GLM. Use this when: - You need to ask a question to an AI model - You want to continue an existing conversation (provide conversation_id) - You need answers from specific AI models like DeepSeek, Grok, or GLM Returns: JSON response containing the conversation ID and the generated answer.

輸入參數modelpresetquestion必填statefulreferencesconversation_id

aichat_create_conversation_v2

Create/manage conversations via AiChat v2 endpoint.

輸入參數idasynclimitmodeltitleactionoffsetpresetmessageuser_idmessagesquestion另有 10 個

aichat_list_models

List all available AI models for the AiChat API. Returns a comprehensive list of supported models grouped by provider, including GPT-4/5, o-series, DeepSeek, Grok, and GLM models. Returns: Formatted list of available models with descriptions.

無需輸入參數。

aichat_get_usage_guide

Get a comprehensive guide for using the AiChat tools. Provides detailed information on how to use the AiChat tools effectively, including parameters, examples, and best practices. Returns: Complete usage guide for AiChat tools.

無需輸入參數。

版本歷史

23
  1. v2026.11.1.3最新Nov 1, 2026
  2. v2026.11.1.1Nov 1, 2026
  3. v2026.10.31.1Nov 1, 2026
  4. v2026.10.31.0Oct 31, 2026
  5. v2026.10.28.1Oct 29, 2026
  6. v2026.10.25.1Oct 26, 2026
  7. v2026.10.25.0Oct 25, 2026
  8. v2026.10.19.1Oct 19, 2026
  9. v2026.10.19.0Oct 19, 2026
  10. v2026.10.18.1Oct 18, 2026
  11. v2026.10.18.0Oct 18, 2026
  12. v2026.10.12.1Oct 12, 2026
  13. v2026.10.8.0Oct 8, 2026
  14. v2026.10.7.1Oct 7, 2026
  15. v2026.10.7.0Oct 7, 2026
  16. v2026.10.6.2Oct 6, 2026
  17. v2026.10.6.0Oct 6, 2026
  18. v2026.10.4.1Oct 4, 2026
  19. v2026.10.4.0Oct 4, 2026
  20. v2026.9.30.2Sep 30, 2026
  21. v2026.9.29.0Sep 29, 2026
  22. v2026.9.24.0Sep 24, 2026
  23. v2026.9.6.1Sep 16, 2026

評分

已滿足適用檢查項的 100%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分