Mcp-ChatBI

5ire is a cross-platform desktop AI assistant, MCP client. It compatible with major service providers, supports local knowledge base and tools via model context protocol servers .

Gateway connector between LLM agents and world data. Official Model Context Protocol server for the Sugra API, backed by a bundled endpoint catalog and operation_id calls. Works with Anthropic Claude, OpenAI GPT, Google Gemini, xAI, and any MCP-enabled IDE. Client details: Anthropic Claude: Claude Desktop, Claude Code (CLI), claude.ai (web) OpenAI GPT: ChatGPT (via MCP connector) Google Gemini: Gemini CLI, Gemini Code Assist (VS Code + JetBrains) xAI: Remote MCP Tools in xAI SDK and Responses API IDEs: VS Code (native), Cursor, Zed, Cline, Continue.dev, Windsurf Custom agents: anything built on the Python or TypeScript MCP SDK

Open-source AI Agent for VS Code and JetBrains that autonomously solves coding tasks end-to-end.

ChatMCP is an AI chat client implementing the Model Context Protocol (MCP).

MCP (Model Context Protocol) Server for Sychev Lab - provides access to products, articles, tutorials, and e-commerce features located in https://lab.sychve.xyz

A transparent desktop overlay that gives your AI agent a visual presence on screen. Your AI picks its own body from a library of avatars, colors, and expressions or draws it's own in SVG. Windows, $4.99, 7-day free trial, no account required.

Rust MCP server that gives AI agents reliable web access. Bypasses Cloudflare and bot protection using Chrome-level TLS fingerprinting, no headless browser needed. 10 tools for scraping, crawling, search, structured extraction, summarization, and more. Output is clean markdown optimized for LLMs with 67% fewer tokens than raw HTML. 8 of 10 tools work locally without an API key.

Conenct your ads to claude Supporting all ads channels (Google Ads, Linkedin Ads, Meta Ads, TikTok Ads) + GA4 and GTM

Explorer-first MCP client that renders any MCP server's tools as interactive UI — no LLM required, no tool-calling loop. Point it at any MCP server over stdio or SSE and get cards, tables, charts, forms, pipelines, and dashboards auto-generated from your tool outputs. Install with `npx burnish -- <your-mcp-server>`.

Advanced multimodal AI music generator with realistic vocals and pro-level arrangements.

Creative AI art engine designed for unique style transfers and instant visual magic.

An MCP server that gives AI assistants access to your Copilot Money personal finance data. It reads from the locally cached Firestore database (LevelDB + Protocol Buffers) on your Mac. Reads are 100% local with zero network requests. 17 read tools across spending, investments, budgets, goals, and more — query transactions, accounts, holdings, balances, categories, recurring charges, budgets, goals, and investment performance. There's also write tools (optional with the flag)

Studio is where you run MCP tools in the browser against real credentials -- see inputs, outputs, and errors before you trust an agent. Enable bundles in your workspace, then add your Hub or per-bundle streamable HTTP URL in Cursor, Claude, ChatGPT, or VS Code. Workspace-scoped credentials; optional mcpbundles CLI on PyPI.

The second fastest AI chatbot™

HyperChat is a Chat client that strives for openness, utilizing APIs from various LLMs to achieve the best Chat experience, as well as implementing productivity tools through the MCP protocol.

One hosted MCP endpoint for a large catalog of production integrations—CRM, billing, data, dev tools, and more. Connect OAuth or API keys in the dashboard, then use one MCP URL (Hub or per-bundle) in Cursor, Claude, or other MCP clients. Includes workspace-scoped credentials, the open-source mcpbundles CLI on PyPI, and optional code-execution tools on the Hub.

A Tiny Terminal Chat App for AI Models with MCP Client Support

MCPwner is a Model Context Protocol (MCP) server that integrates security testing tools into LLM-driven workflows. It provides a unified interface for secret scanning, static analysis (SAST), software composition analysis (SCA), and vulnerability research including 0-day discovery. Instead of manually chaining tools and pasting outputs into your LLM, MCPwner standardizes and streams results directly into the model's working context. This enables continuous reasoning, correlation, and attack path discovery across the entire security research lifecycle - from identifying known vulnerabilities to uncovering novel attack vectors.