Le Chat AI MCP

io.github.rocnubie由 GitHub 账号 rocnubie 发布v0.1.0更新于 Oct 24, 2026

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

已验证STDIO仅桌面知识与记忆AI 与机器学习

概览

AI 生成的概览

一个只读的 MCP 服务器,为助手提供关于 Mistral Le Chat 的参考资料:模型、价格、常见问题与官方链接。

可以做什么
查询站点列出的聊天模型及其能力说明,获取规范的价格入口和官方链接(网站、支持、文档)。读取内置资源,涵盖模型、价格、简短常见问题和规范网址。运行提示词,概述该站点是什么、面向谁,或以默认设置开启针对站点模型的对话评估会话。
适用场景
适合在比较各类 AI 助手、评估 Le Chat 的价格、模型与功能时,在聊天客户端内快速获取参考资料。它是静态指南,并非与 Le Chat 本身的实时连接。
运行要求
以 Node.js 进程通过 stdio 在本地运行;README 给出通过 Smithery 安装或克隆源码后用 node 启动的方式。未声明需要 API 密钥、账户或环境变量。
安装前请注意
内容是关于 Le Chat 的独立第三方指南,并非 Mistral 官方资料,价格和功能细节可能过时,采用前应向厂商核实。该服务器自称只读且无遥测,但它仍是你自行安装并运行的本地进程。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Le Chat AI MCP,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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

来源:README.md,提交 1918743

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.0最新Sep 16, 2026

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