[WIP] Programmable Email

BlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.

Web and local search using Brave's Search API

Read and write email through the Atomic Mail from an AI agent. Handles proof-of-work authentication and JMAP so the agent thinks in JMAP method calls. Use when the user asks to register an email inbox, list mailboxes, fetch or send email.

Taisly Agent is an MCP server, CLI, SDK, and agent skill for publishing short-form videos to TikTok, Instagram Reels, YouTube Shorts, X, and Facebook through Taisly. It helps AI agents and automation workflows validate connected social accounts, create video posts, and check publishing status with a Taisly API key.

AI image generation using various models

Browser automation and web scraping

Is this flight price actually good? Deal oracle for AI agents — remote MCP + REST, backed by real price history on nomad corridors.

OpenFate Bazi MCP is a local Model Context Protocol server for deterministic Chinese Bazi / Four Pillars calculation. It supports True Solar Time correction, solar and lunar calendar input, Day Master, Da Yun luck cycles, branch interactions, reverse Bazi lookup, and transparent calculation metadata. Built on the open-source @openfate/bazi-engine and designed for Claude, Cursor, Codex, and other MCP-compatible agents.

Outcome-aligned AI workflow registry. Design and run AI workflows with verifiers that align an agent to measurable outcomes, with reliable image output.

# debmatic-mcp Connects to a **HomeMatic CCU**'s built-in JSON-RPC API and exposes your devices, rooms, programs, and system variables as MCP tools — **no addons, no XML-API, no cloud**, just a direct connection on your local network. Works with **debmatic**, **CCU3**, and **RaspberryMatic**. ## Features - **25 tools** spanning device control, diagnostics, and configuration - **Read**: list devices/rooms/functions/programs/system variables, read values & paramsets, describe device types, list links - **Control**: set values, run programs, set/create/delete system variables, assign/unassign channels, execute HM-Script - **Diagnostics**: RSSI/radio quality, service messages (read + acknowledge), system info - **Production-hardened**: bearer-token auth with expiry & rotation, optional native TLS, CCU certificate verification (fingerprint pin or CA), rate limiting, DNS-rebinding protection, and structured tool output (`outputSchema`) ## Install ```json { "mcpServers": { "debmatic": { "command": "npx", "args": ["-y", "debmatic-mcp", "--stdio"], "env": { "CCU_HOST": "your-ccu-host", "CCU_PASSWORD": "your-ccu-password" } } } } Configuration Required: CCU_HOST, CCU_PASSWORD Common optional: CCU_USER (default Admin), CCU_HTTPS (default false), CCU_PORT (80/443), CACHE_DIR (default /data) Also runs as a standalone HTTP server (Docker) for networked clients. Full docs in the README. Repo: https://github.com/claymore666/debmatic-mcp · npm: debmatic-mcp · License: MIT

Free AI research/OCR + agent-economy discovery tools (120+ tools, no-auth), includes engage_sasame to commission SaSame to build MCP/Claude/RAG/agents, full deliverables pay-per-call via x402

AI-native HTTP security testing toolkit (MCP server): 17 HTTP tools giving an AI agent low-level control over HTTP/1.1 and HTTP/2 (raw framing, connection pinning, intruder, race, OOB, chains) on its own Go engine. Free tier; docs at rqwstr.com.

summarize chat message

Schedule and publish social media posts to 11+ platforms (X, Instagram, Facebook, TikTok, LinkedIn, YouTube, Threads, Pinterest, Bluesky, Telegram, Google Business Profile) from Claude, ChatGPT, or Cursor. Connect via the hosted OAuth URL (no key, nothing to self-host) or run it locally with npx and your PostFast API key.

Hosted MCP server that gives any AI agent clean, semantically-searchable Reddit (and X) data — read-only, no Reddit API.

One API for Search, Crawling, and Sitemaps

Turn any AI assistant into an expert prompt engineer. Ultra Prompt gives your AI a library of 1,000+ professionally written prompts for real, everyday work, writing, marketing, business, creative, coding, and more. Just describe what you're trying to do, and it finds the right template, fills in the details, and hands back a polished and ready-to-run prompt so you get expert-quality results without wasting time on writing the the best prompt yourself. It can also chain templates into multi-step workflows and save them to reuse anytime. Free to start; works in any MCP client.

A Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.

A Serper MCP Server

基于七牛云产品构建的 Model Context Protocol (MCP) Server，支持用户在 AI 大模型客户端的上下文中通过该 MCP Server 来访问七牛云存储资源、利用 Dora 服务进行图片操作等。 如果有什么需求欢迎在下方评论，您也可以在 github 仓库中提 issue。

Vee3 connects coding agents to a hosted catalog of live data and action tools through one MCP server at `https://mcp.vee3.io/mcp`. Use it for market research, due diligence, competitive analysis, and fact-heavy tasks without leaving your editor. Tools cover domain research (availability, WHOIS, DNS, RDAP, metrics), X (Twitter) search and profiles, Google Trends and keyword insights, SEO and backlinks, Google Maps places, YouTube and TikTok data, Rotten Tomatoes metadata, website screenshots, and free catalog discovery helpers. Sign up at [app.vee3.io](https://app.vee3.io) for a free tier. Tool calls use token-based billing; failed calls are not charged.

Sendmux is an email inbox API and email API for AI agents. Use this MCP server to let authorised agents work with Sendmux mailboxes, inbound email, clean JSON parsing, webhooks, outbound sending, provider routing, logs, billing, and team controls. Agents can read mailbox messages, send email, manage domains and mailboxes, inspect usage, and build multi-tenant email workflows without raw IMAP/SMTP plumbing. Learn more: https://sendmux.ai/product/inboxes MCP setup: https://sendmux.ai/docs/guides/mcp

GitLab API, enabling project management

Playwright MCP server

ATC brings account intelligence into Claude and other AI agents, built on two decades of institutional technology research originally developed for major tech investors. Sales and marketing teams can prioritize accounts, surface buying signals, prep for calls, draft outreach, and build competitive positioning and campaign audiences — grounded in proprietary adoption and initiative data rather than generic firmographics. There's no new UI to learn: ask in natural language and the connector runs the analysis.

Pay-per-call German/EU energy intelligence for AI agents: prices, carbon intensity, grid load, renewables, battery arbitrage, charging decisions. USDC on Base.

Pay-per-call x402 MCP data layer for AI agents. One endpoint, no API keys, USDC settlement on Base.

A Model Context Protocol (MCP) server for creating, managing, and executing Bruno API testing collections. Supports both .bru and .yml (opencollection) formats with built-in security hardening. Why This MCP Server? Use this when you want an AI agent (Claude, Copilot, etc.) to create, inspect, or execute Bruno API test collections programmatically — without opening the Bruno GUI or installing the Bruno CLI. Typical use cases: AI-assisted test generation, CI pipeline integration, automated API exploration. Requires Node.js >= 18.0.0. Features: - Collection Management: Create and organize Bruno collections - Environment Configuration: Manage multiple environments (dev, staging, prod) - Request Generation: Generate request files for all HTTP methods - Authentication Support: Bearer, Basic, OAuth 2.0, API key, Digest - Test Scripts: Add pre/post request scripts and assertions - CRUD Operations: Generate complete CRUD request sets - Collection Statistics: Analyze existing collections - Dual Format Support: .bru (legacy) and .yml (opencollection YAML) with auto-detection - Collection Discovery: Discover Bruno collections from workspace with zero config - Request Modification: Partial-merge updates to existing request files - Variable Chaining: bru.setVar()/bru.getVar() for cross-request variable flow - Dependency Ordering: Topological sort for test suite execution order - Request Execution: Execute requests and run tests with structured results - Security Hardening: SSRF protection, path traversal prevention, VM sandbox for test scripts

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.