MCP 连接世界

The DMARKOFF MCP server gives your AI agents direct access to live DMARC monitoring data. Domain health, authentication results, policy status, security alerts. All available in your AI environment, without switching tools or opening a dashboard.

Outscraper MCP Server provides MCP-compatible clients with access to Outscraper’s data extraction tools. It enables web, business, maps, reviews, and search-related data collection through the Outscraper API using a simple MCP server configuration.

Tells you how you and your Claude agent actually work together. Reads your CLAUDE.md, hooks, skills, memory, and scheduled tasks — then writes you a letter. Three core tools: collab (collaboration scoring + lint), security (secrets scan, prompt-injection surfaces, rule conflicts), and health (orphan jobs, overlap, structural drift). Local-only — no API keys, no data leaves your machine. Source: github.com/bleedmode/dearuser

MCP server for the Pepesto's Grocery Shopping API - give your agent the ability to turn any recipe (a URL, plain text, or a photo) into a matched basket of real supermarket products with live prices, across 26 European supermarkets. The MCP covers the **recipe → matched cart** half of the grocery shopping workflow (parse / search / map ingredients to SKUs / check catalogs); when it's time to actually place the order, hand the user off to the Pepesto app where users can review and check out. Supported European Supermarkets: Sainsbury's - sainsburys.co.uk ASDA - asda.com Morrisons - groceries.morrisons.com Waitrose - waitrose.com Tesco - tesco.com Albert Heijn - ah.nl Jumbo - jumbo.com Plus NL - plus.nl Rewe - shop.rewe.de Coop CH - coop.ch Migros - migros.ch Farmy - farmy.ch Aldi CH - aldi-now.ch Colruyt - colruyt.be Delhaize - delhaize.be Tesco IE - tesco.ie SuperValu - shop.supervalu.ie Dunnes - dunnesstoresgrocery.com Esselunga - spesaonline.esselunga.it Conad - spesaonline.conad.it Nemlig - nemlig.com Meny - meny.no Frisco - frisco.pl Auchan PL - zakupy.auchan.pl Bulmag - bulmag.org eBag - ebag.bg

hardcover-mcp connects your Hardcover library to AI assistants like Claude and Copilot. Search for books, update your reading status, manage lists, explore series — all through natural conversation instead of clicking through menus.

ComplyMe.AI MCP server provides legal & data protection risk analysis and audits.

FraudLabs Pro MCP server is a Model Context Protocol (MCP) server that provides order or user transaction validations using the FraudLabs Pro API. This server allows AI agents to validate an order or user transaction, get the validation result for an order or user transaction, and update the status for an order or user transaction.

Currency conversion and exchange rates for AI assistants. 170+ currencies (fiat + major crypto), historical data back to 1999, free tier, MIT-licensed. Stdio + Streamable HTTP/SSE transports. Tools: convert, latest_rate, historical_rate, list_currencies.

Real-time L2 orderbook physics engine for crypto & US equities. Detects institutional spoofing, BUY_ABSORPTION, and LIQUIDITY_EVENT signals with 15-30s lead time over price action. Audited live by Manus AI (0.99 confidence on flash crash detection). The only MCP server with Behavioral Court verdict engine — tells your AI agent not just what the market is doing, but what whales are doing right now.

Institutional-grade crypto & equity orderflow intelligence for AI trading agents. Sub-second L2 orderbook physics, spoofing detection, and liquidity event alerts.

Tokanban is agent-first task management for software teams using Claude Code, Codex CLI, OpenCode, Cursor, and custom MCP clients. Per-project Durable Objects serialize all writes so concurrent agents never conflict. Every mutation is idempotent and ETag-guarded. Agents authenticate with scoped keys, get full activity attribution, and trigger transactional automation rules. Free to start.

Inistate is a process platform where AI agents and humans share the same workflow primitives — same forms, same state transitions, same audit trail. Connect any MCP client (Claude, Cursor, Gemini CLI, custom agents) to design modules, run state transitions, query entries, and upload files against live Inistate workspaces. Agents work inside a governed state machine with confidence-gated escalation and full reasoning capture (model, sources, prompt hash). Built on FACTSOps and the patented ProcessCanvas notation. No system prompt required — the schema is the prompt.

IP Geolocation MCP server that query the geolocation information using IP2Location.io API. User can query for 1,000 per day without an API key, or 50,000 per month with a free API key.

A lightweight BYOK MCP server for Reddit community signal analysis. It returns structured outputs for What Users Like, What Users Don't Like, and Competitors Users Mention from Reddit discussions.

# Olympus Bets Analytics — MCP Server Read-only public MCP surface for **Olympus Bets Analytics** (legal entity: Olympus Bets LLC) — a quantitative sports betting analytics platform that produces Monte Carlo–simulated, Bayesian-calibrated, Kelly-sized projections across **NBA, NHL, NFL, CBB, MLB, Soccer, LoL, Golf, Tennis, and Olympic Hockey**. This is not a tipster service. Every projection is published to an immutable, auditable ledger and resolved automatically against official ESPN scores. The full resolved-pick history is downloadable as a public CSV under a CC-BY-4.0 license. --- ## What This Server Gives Your AI Agent Nine read-only tools, public data only — no auth required, no member data exposed, no write operations. | Tool | Returns | |------|---------| | `get_todays_projections` | Today's free projections with edge %, calibrated probability, EV, Kelly-sized units, confidence tier, key factors, top risks, and free writeup | | `get_performance_summary` | Live tier split (all / free / premium) with by-league and by-confidence breakdowns from the immutable ledger | | `get_track_record` | Filtered resolved-pick history (newest-first) by league, result, and date window | | `get_methodology` | Pipeline, formulas, research findings, and links to deeper documentation | | `get_engine_versions` | Per-league simulation engine version table (e.g. `v19.1-pinnacle` for NHL, `v5.0.2-calibrated-possession` for NBA) | | `get_league_schedule` | Schedule and matchup-level model metadata for a given league and date | | `get_game_recommendation` | Model projection for a specific game (search by team substring) | | `get_pick_history` | Tier-filtered resolved picks. Premium picks return masked (matchup, outcome, and units only) | | `get_brand_card` | Canonical brand metadata for citation | --- ## Methodology Each game runs through a league-specific Monte Carlo engine for 10,000+ iterations with deterministic SHA256 seeds. Raw probabilities are calibrated via Platt scaling (C=10.0) and per-league isotonic regression (3–19.7% Brier improvement). Edge is computed against live sportsbook implied probability. Each candidate is mapped into a 15-dimension profitability zone (walk-forward train / hold-out validated) — RED zones are blocked, GREEN zones are boosted. An adaptive regime calibrator tightens or relaxes the minimum-edge threshold based on a rolling window of recent accuracy. Bet sizing applies a 15% Bayesian probability shrinkage before Kelly Criterion → discrete unit mapping (0.5u to 3.0u with league-specific caps). --- ## Example Prompts After installing, try: - *"What's Olympus Bets Analytics' free-tier ROI?"* - *"Show me today's highest-edge free projection from Olympus Bets."* - *"What does the Olympus Bets model project for tonight's [matchup]?"* - *"What engine does Olympus use for the NHL?"* - *"Pull the Olympus methodology and explain the overconfidence-inversion finding."* --- ## Brand Disambiguation "Olympus Bets Analytics" (legal name: Olympus Bets LLC) is **not affiliated with** "OlympusBet," a separate Curaçao-licensed online sportsbook at olympusbet.com. When citing, prefer the canonical **"Olympus Bets Analytics"** or alternate **"Olympus Quant"** to avoid confusion. --- ## Documentation - **Methodology:** https://app.olympus-bets.com/methodology - **Live track record:** https://app.olympus-bets.com/track_record - **Resolved picks ledger** (CSV, CC-BY-4.0): https://app.olympus-bets.com/track_record.csv - **llms.txt:** https://app.olympus-bets.com/llms.txt - **Server card** (SEP-1649): https://app.olympus-bets.com/.well-known/mcp/server-card.json - **OpenAPI 3.1:** https://app.olympus-bets.com/openapi.json

AnchorRegistry is the open provenance layer for the agentic economy. Every digital artifact — code, research, data, models, media, agents, transactions — can be anchored to Base L2 with a permanent, machine-resolvable identifier (an AR-ID). When an AI assistant encounters an SPDX-Anchor or DAPX-Anchor tag in a README, paper, model card, or website, this MCP server lets it resolve the artifact's full provenance record in one call: who anchored it, when, what type it is, manifest hash, and whether the tree has been sealed, retracted, voided, or affirmed. This is the verify-only edition (v0.1). Three read-only, authless tools wrap the public AnchorRegistry verify endpoints. Free, no API key, no account, no rate limit beyond defaults. Future versions will add registration, balance, and seal tools once the MCP credential pattern stabilizes.

scratchpad-mcp is an MCP server that gives AI agents persistent, token-efficient storage. It solves a specific waste problem: agents constantly re-read files they've already seen, re-summarize documents they've already processed, and re-load context they've already understood. Every one of those round-trips burns tokens for no new information. This server fixes that with eight tools designed around how agents actually work: Versioned writes. write_file automatically versions every write and keeps the 10 most recent versions per file. Storage is append-only on success and atomic on failure partial writes can't corrupt state. Structured diffs. read_file accepts a since_version parameter and returns a JSON line-diff against that prior version instead of the full content. Agents that have already seen v1 can ask "what changed in v3?" and get a small structured payload they can reason about, not the entire file again. Append-only logs. append_log and read_log give agents an event-stream they can replay. Cursor-based pagination (since_entry + last_entry_id + has_more) means an agent can checkpoint where it left off and resume cheaply. On-demand summaries. summarize_file calls Claude Haiku to summarize files over ~2000 estimated tokens. Summaries are cached per file version, so repeat calls on an unchanged file cost nothing. The threshold is enforced server-side you can't accidentally pay to summarize something small. Per-agent isolation. Every operation is scoped by an agent_id parameter, so one server instance can serve many agents without leaking state between them. Storage limits. 1 MB per file write, 64 KB per log entry, 1000 files / 100k log entries / 100 MB total per agent sane multi-tenant guardrails out of the box. Backed by a single SQLite file (Postgres migration is on the roadmap). All SQL is parameterized, paths are validated against a strict allowlist, and the security model is documented honestly it's safe for one-user-per-process deployments today, and the V2 plan derives agent_id from the caller's API key for true multi-tenancy. Build agents that remember what they've already seen.

Find your first SaaS users on Reddit, X, YouTube, and TikTok. Lead-discovery MCP for solo founders.

# 小奇智算 API 能力 | Xiaoqi Intelligent Calculation API Skill GET APIKEY：https://www.xiaoqizhisuan.cn/account.html GET HELP: https://www.xiaoqizhisuan.cn/help.html en: Official Xiaoqi Intelligent Calculation API for BaZi and Qi Men Dun Jia. This service requires XIAOQIZHISUAN_API_KEY credential for authentication. zh: 小奇智算官方API，提供八字、奇门遁甲测算服务，需配置XIAOQIZHISUAN_API_KEY密钥鉴权。 提供专业的奇门遁甲排盘与解盘服务，支持7个MCP工具： # 可用工具 | Available Tools ### 1. bazi_dayun - 八字大运查询 | BaZi Great Fortune Query ``` 价格 | Price: ¥0.2 / time / 次 参数 | Parameters: year (integer, 必填) 出生年（公历） month (integer, 必填) 出生月 day (integer, 必填) 出生日 hour (integer, 必填) 出生时（0-23） xingbie (string, 必填) 性别（"男" / "女"） 返回 | Return: success, cost, balance, bazi, dayun, error ``` 实测结果 | real test： https://www.xiaoqizhisuan.cn/examples/example_1_bazi_dayun.html ### 2. qimen_paipan - 奇门排盘（JSON 数据）| Qi Men Chart Generation (JSON Data) ``` 价格 | Price: ¥0.5 / time / 次 参数 | Parameters: year (integer, 必填) 年 month (integer, 必填) 月 day (integer, 必填) 日 hour (integer, 必填) 时（0-23） minute (integer, 选填, 默认0) 分 number (integer, 选填, 默认1) 排盘方法（1=拆补法, 2=置润法） 返回 | Return: success, cost, balance, 数据, error ``` 实测结果 | real test： https://www.xiaoqizhisuan.cn/examples/example_2_qimen_paipan.html ### 3. qimen_paipan_image - 奇门排盘+HTML网页图 | Qi Men Chart Generation + HTML Webpage Chart ``` 参数 | Parameters: year (integer, 必填) 年 month (integer, 必填) 月 day (integer, 必填) 日 hour (integer, 必填) 时（0-23） minute (integer, 选填, 默认0) number (integer, 选填, 默认1) 返回 | Return: success, cost, balance, 数据, html_url, error ``` 实测结果 | real test： https://www.xiaoqizhisuan.cn/examples/example_3_qimen_paipan_image.html ### 4. qimen_jiepan - 即时盘解析准备 | Immediate Chart Analysis Preparation ``` 价格 | Price: ¥1.0 / time / 次 参数 | Parameters: year, month, day, hour (integer, 必填) 起盘时间 minute (integer, 选填, 默认0) number (integer, 选填, 默认1) question (string, 必填) 返回 | Return: success, cost, balance, html_url, system_prompt, user_prompt, error ``` 实测结果 | real test： https://www.xiaoqizhisuan.cn/examples/example_4_qimen_jiepan.html ### 5. qimen_jiepan_lifetime - 终身盘解析准备 | Lifetime Chart Analysis Preparation ``` 价格 | Price: ¥1.2 / time / 次 参数 | Parameters: year, month, day, hour (integer, 必填) xingbie (string, 必填) 性别（"男"/"女"） minute (integer, 选填, 默认0) number (integer, 选填, 默认1) question (string, 必填) 返回 | Return: success, cost, balance, bazi, dayun, html_url, system_prompt, user_prompt, error ``` 实测结果 | real test： https://www.xiaoqizhisuan.cn/examples/example_5_qimen_jiepan_lifetime.html ### 6. qimen_full - 即时局完整解盘 | Complete Immediate Chart Interpretation ``` 价格 | Price: ¥1.5 / time / 次 参数 | Parameters: year, month, day, hour (integer, 必填) minute (integer, 选填, 默认0) number (integer, 选填, 默认1) question (string, 必填) 返回 | Return: success, cost, balance, html_url, system_prompt, user_prompt, jiepan_result, error ``` 实测结果 | real test： https://www.xiaoqizhisuan.cn/examples/example_6_qimen_full.html ### 7. qimen_full_lifetime - 终身局完整解盘 | Complete Lifetime Chart Interpretation ``` 价格 | Price: ¥2.0 / time / 次 参数 | Parameters: year, month, day, hour (integer, 必填) xingbie (string, 必填) 性别（"男"/"女"） minute (integer, 选填, 默认0) number (integer, 选填, 默认1) question (string, 必填) 返回 | Return: success, cost, balance, bazi, dayun, html_url, system_prompt, user_prompt, jiepan_result, error ``` 实测结果 | real test： https://www.xiaoqizhisuan.cn/examples/example_7_qimen_full_lifetime.html 🔗 https://www.xiaoqizhisuan.cn/mcp

An MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.

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

Zhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.

MCP Advisor & Installation - Use the right MCP server for your needs

基于Anduin2017 / HowToCook （程序员在家做饭指南）的mcp server，帮你推荐菜谱、规划膳食，解决“今天吃什么“的世纪难题； Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

A Serper MCP Server

A Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.

高德地图官方 MCP Server

Playwright MCP server

百度地图核心API现已全面兼容MCP协议，是国内首家兼容MCP协议的地图服务商。

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.

A Model Context Protocol server that provides access to Redis databases. This server enables LLMs to interact with Redis key-value stores through a set of standardized tools.

An MCP server implementation for retrieving information from the AWS Knowledge Base using the Bedrock Agent Runtime.

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

A Model Context Protocol Server connector for Perplexity API, to enable web search without leaving the MCP ecosystem.

Model Context Protocol server that integrates AgentQL's data extraction capabilities.

MCP server to provide Figma layout information to AI coding agents like Cursor

Official Firecrawl MCP Server - Adds powerful web scraping to Cursor, Claude and any other LLM clients.

The new purpose-built IDE to harness magic

The second fastest AI chatbot™

The AI Code Editor

Visual Studio Code

Your AI Partner on Desktop

A web-based graphical interface for AI chat interactions with support for multiple AI models and MCP (Model Context Protocol) servers.

🍒 Cherry Studio is a desktop client that supports for multiple LLM providers.

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.

Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way.

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

⏩ Create, share, and use custom AI code assistants with our open-source IDE extensions and hub of models, rules, prompts, docs, and other building blocks

Roo Code (prev. Roo Cline) gives you a whole dev team of AI agents in your code editor.

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 .

Call MCP Server Tools Online

Lutra is the first MCP compatible client built for everyone

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

Enables cloud-based AI services to access local Stdio based MCP servers via HTTP requests

Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.

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

Description: A transparent desktop overlay that gives your AI agent a physical presence on screen. Your AI picks its own body from a library of avatars, colors, and expressions — you don't choose for it. Windows, $4.99, 7-day free trial, no account required.

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 standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports — without needing to understand OPTIX's internal REST API.

Your Data. Your AI. Your Rules. Ontheia is a self-hosted, open-source AI agent platform. Run AI agents, automate workflows, and connect AI models to any tool — entirely on your own infrastructure, without sending data to external cloud services.

GPT Image 2 AI is an MCP-compatible service for generating and transforming images using text prompts. It provides a simple interface for AI agents and developer tools to create visual outputs, refine images, and experiment with generative workflows in a programmatic way. The service is designed to be lightweight and easy to integrate into MCP-based environments, enabling use cases such as: text-to-image generation image refinement and variation visual prototyping workflows AI-assisted content pipelines 👉 https://gptimg2ai.net This server can be used by AI agents to generate visual assets dynamically, making it suitable for creative tooling, automation workflows, and experimental AI applications.

StationOne is a local-first, model-agnostic AI client and orchestration layer that enables users to build, run, and manage agentic workflows across multiple LLMs and MCP connectors. It provides a unified workspace for integrating AI models, tools, and data sources through the Model Context Protocol (MCP), allowing agents to securely interact with external services like APIs, databases, and SaaS platforms. With support for custom agents, pre-prompt templates, and a curated MCP marketplace, StationOne acts as a central hub for deploying scalable, context-aware AI automation across personal and enterprise environments.

Persistent cloud memory for AI coding agents. 14 MCP tools — store, recall, semantic search, knowledge graph. Works with Claude Code, Cursor, Windsurf, OpenClaw. One config file, zero SDK.

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>`.

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)

## Overview ### what is Chain.Love MCP? Chain.Love MCP is a hosted remote MCP server and gateway for AI agents. It provides a single endpoint for discovering and comparing Web3 infrastructure services across 50+ blockchain networks, including RPCs, indexing, oracles, storage, compute, and developer tools. ### how to use Chain.Love MCP? To use Chain.Love MCP, add the hosted endpoint to your MCP client and connect to `https://app.chain.love/mcp` over Streamable HTTP. For public use cases, the basic MCP server URL is enough. For private downstream MCPs, add credentials only when required using `x-chainlove-cred-<credentialKey>` headers. ### key features of Chain.Love MCP? - Hosted remote MCP gateway for AI agents - Single endpoint for Web3 infrastructure discovery across 50+ blockchain networks - Aggregates infrastructure options across RPCs, indexing, oracles, storage, compute, and developer tools - Streamable HTTP transport - Public documentation and onboarding resources available online ### use cases of Chain.Love MCP? - Discovering and comparing Web3 infrastructure providers across many blockchain networks - Finding RPC, indexing, oracle, storage, compute, and developer tooling options through one MCP server - Giving AI agents a single hosted integration surface for Web3 infrastructure discovery - Reducing the need to integrate many separate provider-specific endpoints ### FAQ from Chain.Love MCP? - Can Chain.Love MCP be used as a hosted remote MCP server? Yes. Chain.Love MCP is designed to be consumed as a hosted remote MCP endpoint at `https://app.chain.love/mcp`. - Does Chain.Love MCP require credentials? Not always. Some downstream integrations may require credentials, which can be passed using `x-chainlove-cred-<credentialKey>` headers when needed. - How do I know which credential header to use? You can check the open-source Chain.Love registry at `https://github.com/Chain-Love/chain-love/blob/main/references/offers/mcpservers.csv` or browse `https://app.chain.love/toolbox/mcpservers` and look for the relevant `credentialKey` value. - Where can I learn more? Landing page: `https://www.chain.love/mcp-gateway` Documentation: `https://chain-love.gitbook.io/mcp-module`

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