Mcp Aichat

io.github.AceDataCloudPublished by GitHub account AceDataCloudv2026.11.1.3Updated Nov 3, 2026

MCP server for AI dialogue using various LLM models via AceDataCloud

VerifiedStreamable HTTPWeb executableCommunication & CollaborationAI & ML

Overview

AI-generated overview

AceDataCloud's AiChat MCP server lets an assistant send questions to many hosted LLM models and keep multi-turn conversations.

What you can do
  • Ask questions to a chosen model and get generated answers, with multi-turn continuation via conversation IDs
  • Run the v2 conversation endpoint with agent-style iterations and optional server-side state
  • List available models grouped by provider, such as OpenAI, DeepSeek, xAI, Zhipu, Gemini and Kimi
  • Retrieve a usage guide describing parameters, examples and best practices
When to use it
Useful when you want one MCP connection that reaches several model families (GPT, o-series, DeepSeek, Grok, GLM, Gemini, Kimi) without wiring each provider separately, or when you want server-side conversation state and reference sources for context-aware answers.
Requirements
Either the hosted endpoint with OAuth sign-in to an AceDataCloud account, or an AceDataCloud API token sent as a Bearer header; or the local PyPI package mcp-aichat run with uvx or pip, with ACEDATACLOUD_API_TOKEN set. Network access to the AceDataCloud API is always required.
Before you install
The hosted service can be metered and each model call is billed by actual usage, so check pricing and account balance first. The API token is a secret: keep it in a credential store or environment variable, never in prompts, shared configs or commits, and do not combine OAuth login with a fixed Authorization header. Requests and prompts go to AceDataCloud as a third party, and a listed tool or submitted task does not prove a successful result.

Installation

In SourceWeft

  1. Open Mcp Aichat in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.AceDataCloud%2Fmcp-aichat/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "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.

Source: README.md at commit 248329f

Tools

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.

Parametersmodelpresetquestionrequiredstatefulreferencesconversation_id

aichat_create_conversation_v2

Create/manage conversations via AiChat v2 endpoint.

Parametersidasynclimitmodeltitleactionoffsetpresetmessageuser_idmessagesquestion+10 more

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.

Takes no parameters.

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.

Takes no parameters.

Version history

23
  1. v2026.11.1.3LatestNov 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

Score

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