Le Chat AI MCP

io.github.rocnubie由 GitHub 帳號 rocnubie 發布v0.1.0更新於 Oct 24, 2026

Le Chat AI walks through Mistral's Le Chat - Free/Pro/Team pricing, Flash Answers, Deep Research,

已驗證STDIO僅桌面知識與記憶AI 與機器學習

概覽

AI 產生的概覽

一個唯讀的 MCP 伺服器,為助理提供關於 Mistral Le Chat 的參考資料:模型、價格、常見問題與官方連結。

可以做什麼
查詢站點列出的聊天模型及其能力說明,取得標準的價格入口與官方連結(網站、支援、文件)。讀取內建資源,涵蓋模型、價格、簡短常見問題與標準網址。執行提示詞,概述該網站是什麼、適合誰,或以預設設定開啟針對站點模型的對話評估工作階段。
適用情境
適合在比較各種 AI 助理、評估 Le Chat 的價格、模型與功能時,在聊天用戶端內快速取得參考資料。它是靜態指南,並非與 Le Chat 本身的即時連線。
執行需求
以 Node.js 程序透過 stdio 在本機執行;README 提供透過 Smithery 安裝或複製原始碼後以 node 啟動的方式。未宣告需要 API 金鑰、帳號或環境變數。
安裝前請注意
內容是關於 Le Chat 的獨立第三方指南,並非 Mistral 官方資料,價格與功能細節可能過時,採用前應向廠商確認。此伺服器自稱唯讀且無遙測,但它仍是你自行安裝並執行的本機程序。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Le Chat AI MCP,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Le Chat AI MCP Server

Le Chat AI: Independent guide to Mistral's Le Chat

[MCP Badge] [Node] [Stdio Transport] [Zero Config] [smithery] [License: MIT] [MCP]

[Le Chat AI]

A Model Context Protocol server that exposes the canonical Le Chat AI knowledge surface — models, prompts, and chat workflows, pricing, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.

Official website: https://lechatai.online

💬 About Le Chat AI

LeChat AI (lechatai.online) is an independent guide and resource hub for Mistral's Le Chat conversational AI platform. The site covers the platform's capabilities in depth — from its speed benchmarks and pricing tiers to its European data compliance stance and open-weight model philosophy. Visitors can read structured comparisons, tutorials, and feature breakdowns, and follow direct links to test Le Chat themselves. The content is oriented toward helping individuals and organizations evaluate whether Le Chat fits their needs, particularly those comparing it against ChatGPT, Claude, Gemini, or other mainstream AI assistants.

Key Features

  • Flash Answers: Near-instantaneous response generation powered by Cerebras WSE-3 hardware, reaching approximately 1,000 tokens per second — one of the fastest inference speeds available in a consumer-facing AI product.
  • Deep Research: An automated research mode that synthesizes information from multiple sources and returns structured, cited reports — suited for market analysis, academic literature reviews, and competitive comparisons.
  • Document analysis: Native support for large PDF imports (50+ pages) with summarization and in-line citation, allowing users to interrogate long documents without manual reading.
  • MCP connectors: Over 20 integrations with third-party platforms including GitHub, Snowflake, and Atlassian, enabling Le Chat to pull live data from internal systems during conversations.
  • Memories: Persistent cross-session context so the assistant retains relevant preferences and prior conversation details over time.
  • Canvas workspace: A collaborative, document-style workspace for drafting and iterating on longer-form outputs alongside the assistant.
  • No Telemetry mode: Available on the Pro tier, this option disables usage data collection — a meaningful option for privacy-conscious teams.

Use Cases

  • Enterprise research workflows: Teams use Deep Research to produce sourced briefings on competitors, technologies, or regulatory landscapes without manual aggregation.
  • Document review: Legal, compliance, and finance professionals import large PDFs and ask targeted questions, receiving cited answers rather than raw text.
  • Developer tooling: Engineering teams connect Le Chat to GitHub or internal databases via MCP connectors to query codebases, pull request histories, or data pipelines in natural language.
  • Privacy-first AI adoption: European organizations subject to GDPR constraints evaluate Le Chat as a compliant alternative to US-hosted AI services, with EU data residency and telemetry controls.
  • AI platform comparison: Individuals and procurement teams use the site's structured breakdowns to compare Le Chat's pricing (approximately $14.99/month for Pro) and capabilities against competing platforms before committing.

Who Is It For

The primary audience is professionals and organizations already using or evaluating AI assistants who want a clear, detailed picture of what Le Chat offers. This includes enterprise IT and procurement teams assessing compliance requirements, developers looking for open-weight model deployability, and European companies that need GDPR-aligned tools with EU data hosting. It also serves individual power users who care about response speed, document handling depth, or third-party integrations — and who want a straightforward comparison rather than marketing material. The site assumes some familiarity with conversational AI but does not require technical expertise.

Tools

list_models

Return the canonical list of chat models exposed on the site, with capability notes. (Le Chat AI)

Input: no parameters. Returns: text/markdown.

get_pricing

Return the canonical pricing entry point for Le Chat AI.

Input: no parameters. Returns: text/markdown.

get_official_links

Return the canonical list of official links for Le Chat AI (website, support, docs when available).

Input: no parameters. Returns: text/markdown.

Resources

  • site://lechatai/models — Supported chat models and capability notes.
  • site://lechatai/pricing — Canonical pricing entry point.
  • site://lechatai/faq — Short FAQ generated from public site metadata.
  • site://lechatai/links — Canonical URLs to share with users.

Prompts

tell_me_about_lechatai

Summarize what the site is, who it's for, and how it works. — Le Chat AI

start_chat_session_lechatai

Open a chat-evaluation session against the site's models, with sensible defaults. — Le Chat AI

Installation

Install via Smithery

bash
npx -y @smithery/cli install lechatai-mcp --client claude

(Replace claude with cursor, windsurf, or continue for those clients.)

Install from source

bash
git clone https://github.com/rocnubie/lechatai-mcp.gitcd lechatai-mcppnpm install

Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):

json
{  "mcpServers": {    "lechatai-mcp": {      "command": "node",      "args": [        "/absolute/path/to/lechatai-mcp/src/index.mjs"      ]    }  }}

Debug with MCP Inspector

bash
npx @modelcontextprotocol/inspector node src/index.mjs

Official Links

Development

bash
pnpm installpnpm start                 # run the server over stdio

License

MIT

來源:README.md,提交 1918743

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.0最新Sep 16, 2026

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