发现优秀的 MCP 服务器

jira-helper

MCP server providing tools to read and write Jira Cloud issues, including a bridge to GitHub commits for tracing issues to code.

Azul Logistica MCP

Integrates Azul Cargo Express logistics operations with MCP clients like Shopify and TOTVS Moda, enabling freight quotes, tracking, CTe downloads, remittance issuance/cancellation, and invoice queries through the Azul API using secure authentication and production/homologation environments.

long-context-mcp

An MCP server implementing Recursive Language Models (RLM) to process arbitrarily large contexts through a programmatic probe, recurse, and synthesize loop. It enables LLMs to perform multi-step investigations and evidence-backed extraction across massive file sets without being limited by standard context windows.

super-productivity-mcp

MCP server that connects AI assistants to Super Productivity for managing tasks, projects, and tags through natural language, supporting quick capture, batch triage, and full planning workflows.

telegram-mcp-server

Enables Claude to interact with Telegram channels and groups through API or web scraping for reading posts and searching.

TallyPrime MCP Server

Gives AI models native-level control over TallyPrime ERP, covering 169+ tools across all functional modules including masters, vouchers, reports, GST, payroll, and more.

Cab Service MCP Server

Enables cab booking and management through natural conversation, allowing users to book rides, cancel bookings, and view driver details. Works with Google Maps MCP to provide comprehensive travel planning with automatic route optimization and cab arrangements between destinations.

docs-mcp

Local documentation search server for AI models using hybrid retrieval (phrase, keyword, vector). Provides MCP tools to search and fetch documentation from bundled or custom doc sets without any external API keys.

ClickUp MCP Server

Enables multi-user access to ClickUp workspaces, tasks, comments, custom fields, time tracking, and more through 150 tools, with per-user OAuth authorization.

cyberdyne-mcp

Lets an AI agent hire and pay a verified human: post real-world tasks (voice, observation, judgment) and pay in USDC via a non-custodial x402 auth-capture escrow on Base, budget frozen at deploy. Humans verify their X identity before submitting.

5dive MCP server

Exposes the 5dive agent-fleet CLI (tasks, agents, digest) as stdio MCP tools. MIT.

delivery-intelligence-mcp

Enables delivery leads to query explainable programme health, prioritized risks, dependency impacts, change request effects, blocked decisions, and evidence-backed claims with refusal on unsupported assertions, all via deterministic tools and telemetry.

Velo Payments API MCP Server

An MCP server that enables interaction with Velo Payments APIs for global payment operations, automatically generated using AG2's MCP builder from the Velo Payments OpenAPI specification.

MCP Host Project

Okay, here's a translation of the English text "Showcases how to integrate Spring AI's support for MCP (Model Context Protocol) within Spring Boot applications, covering both server-side and client-side implementations." into Chinese: **Option 1 (More Literal):** 展示如何在 Spring Boot 应用中集成 Spring AI 对 MCP (模型上下文协议) 的支持，涵盖服务端和客户端的实现。 **Option 2 (Slightly More Natural):** 本示例展示如何在 Spring Boot 应用中整合 Spring AI 的 MCP (模型上下文协议) 支持，包括服务端和客户端的实现方式。 **Explanation of Choices:** * **展示 (zhǎnshì) / 本示例 (běn shìlì):** Both mean "showcase" or "demonstrate." "本示例" (this example) is slightly more common in technical documentation. * **集成 (jíchéng) / 整合 (zhěnghé):** Both mean "integrate." "整合" can sometimes imply a more thorough or seamless integration. * **Spring AI 对 MCP (模型上下文协议) 的支持 (Spring AI duì MCP (móxíng shàngxiàwén xiéyì) de zhīchí):** This is a direct translation of "Spring AI's support for MCP (Model Context Protocol)." The Chinese translation of "Model Context Protocol" is "模型上下文协议" (móxíng shàngxiàwén xiéyì). * **涵盖 (hāngài) / 包括 (bāokuò):** Both mean "covering" or "including." * **服务端 (fúwùduān) / 客户端 (kèhùduān):** These are standard translations for "server-side" and "client-side," respectively. * **实现 (shíxiàn) / 实现方式 (shíxiàn fāngshì):** Both mean "implementation." "实现方式" (implementation method/way) is slightly more descriptive. **Recommendation:** I would recommend **Option 2 (Slightly More Natural):** **本示例展示如何在 Spring Boot 应用中整合 Spring AI 的 MCP (模型上下文协议) 支持，包括服务端和客户端的实现方式。** This option sounds a bit more natural and is commonly used in Chinese technical documentation.

paytabs-mcp

MCP server for PayTabs payment gateway (MENA region). Enables payment page creation, transaction management, refunds, voids, tokenization, and payment method discovery.

Semble Code Search Gate MCP

A paid remote MCP server for routing code search queries, providing structured receipts, audit logs, and reviewer-ready evidence.

SEO Performance MCP

A MCP server that turns your scattered SEO and analytics data into one clear verdict per URL. Plug it into Claude, Cursor, or any MCP-aware client and ask: "Which three posts should I update this week?" - and get an answer backed by hard numbers.

mcp-noaa

Provides access to NOAA National Weather Service forecasts and alerts. Enables finding weather observation stations in US states via the get_stations tool.

BlenderMCP

Connects Blender to Claude AI, enabling AI-assisted 3D modeling, scene creation, object manipulation, material control, and code execution directly in Blender through natural language prompts.

cursor_agents

Okay, here are a few ways you could use an MCP (presumably referring to a Media Control Platform or similar system) server to add a team of experts into an agent flow, along with explanations and considerations: **Understanding the Goal** First, let's clarify what "adding a team of experts into the agent flow" means. This likely involves: * **Routing:** Directing specific types of customer interactions (calls, chats, emails) to the appropriate expert(s). * **Escalation:** Transferring an interaction from a general agent to an expert when the agent needs assistance. * **Collaboration:** Allowing agents to consult with experts in real-time (e.g., via chat, conference call) without transferring the customer. * **Knowledge Sharing:** Providing agents with access to expert knowledge bases or documentation. **Methods Using an MCP Server** Here are some common approaches, assuming your MCP server has capabilities like routing, presence management, and integration with other systems: **1. Skill-Based Routing (Most Common)** * **Concept:** Configure the MCP server to route interactions based on the skills required to handle them. The "experts" are defined as having specific skills. * **Implementation:** * **Skill Definition:** Define skills in the MCP server (e.g., "Product A Expert," "Technical Support - Level 2," "Spanish Language"). * **Expert Skill Assignment:** Assign the appropriate skills to each expert agent in the MCP system. * **Routing Rules:** Create routing rules that direct interactions with specific requirements (e.g., "Product A" inquiries) to agents with the "Product A Expert" skill. This often involves analyzing the customer's input (e.g., IVR selections, chat keywords, email subject) to determine the required skills. * **Queue Management:** The MCP server manages queues for each skill. If no experts are immediately available, the interaction is placed in the appropriate queue. * **Advantages:** Efficiently routes interactions to the right experts. Scalable as the team of experts grows. * **Considerations:** Requires accurate skill definition and assignment. Needs a mechanism to determine the required skills for each interaction (e.g., IVR, AI-powered intent analysis). **2. Presence-Based Routing** * **Concept:** Route interactions to experts based on their availability (presence status). * **Implementation:** * **Presence Integration:** The MCP server integrates with the expert's communication tools (e.g., softphone, chat client) to track their presence (available, busy, away, etc.). * **Routing Rules:** Create routing rules that only send interactions to experts who are currently available. * **Overflow Handling:** Define what happens if no experts are available (e.g., send to a general queue, offer a callback). * **Advantages:** Avoids sending interactions to unavailable experts. Improves customer experience. * **Considerations:** Requires reliable presence information. Needs a strategy for handling overflow situations. **3. Escalation/Transfer Functionality** * **Concept:** Allow general agents to transfer interactions to experts when they need assistance. * **Implementation:** * **Transfer Options:** Provide agents with a way to easily transfer interactions to specific experts or to a queue of experts. This might be a button in their agent desktop application. * **Warm Transfer vs. Cold Transfer:** Decide whether the agent should introduce the customer to the expert (warm transfer) or simply transfer the interaction without introduction (cold transfer). * **Context Transfer:** Ensure that relevant information about the interaction (e.g., customer history, previous interactions) is transferred along with the interaction. * **Advantages:** Allows agents to handle a wider range of issues. Provides access to expert knowledge when needed. * **Considerations:** Requires a user-friendly transfer interface. Needs a mechanism to ensure that context is transferred. **4. Collaboration Tools (Consultation)** * **Concept:** Enable agents to consult with experts in real-time without transferring the customer. * **Implementation:** * **Chat Integration:** Integrate a chat system into the agent desktop application that allows agents to communicate with experts. * **Conference Calling:** Allow agents to add experts to a conference call with the customer. * **Screen Sharing:** Enable agents to share their screen with experts for assistance. * **Advantages:** Allows agents to resolve complex issues quickly. Reduces the need for transfers. * **Considerations:** Requires a reliable communication platform. Needs a mechanism to manage expert availability. **5. Knowledge Base Integration** * **Concept:** Provide agents with access to a knowledge base that contains expert knowledge. * **Implementation:** * **Knowledge Base Platform:** Use a knowledge base platform to store and organize expert knowledge. * **Integration with Agent Desktop:** Integrate the knowledge base into the agent desktop application so that agents can easily search for information. * **AI-Powered Search:** Use AI to improve the accuracy and relevance of search results. * **Advantages:** Empowers agents to resolve issues independently. Reduces the need to consult with experts. * **Considerations:** Requires a well-maintained knowledge base. Needs a mechanism to ensure that the knowledge is accurate and up-to-date. **Example Scenario (Skill-Based Routing)** Let's say you have a team of experts who specialize in different products (Product A, Product B, Product C). 1. **Define Skills:** In your MCP server, define skills: "Product A Expert," "Product B Expert," "Product C Expert." 2. **Assign Skills:** Assign the appropriate skills to each expert agent. For example, Agent John might have the "Product A Expert" skill. 3. **Configure IVR:** In your IVR (Interactive Voice Response) system, ask the customer which product they need help with. 4. **Routing Rule:** Create a routing rule in the MCP server that says: "If the customer selects 'Product A' in the IVR, route the call to an agent with the 'Product A Expert' skill." 5. **Queue Management:** If no "Product A Expert" agents are available, the call is placed in a "Product A Expert" queue. **Chinese Translation of Key Terms** Here are some translations of key terms that might be helpful when discussing this with Chinese-speaking colleagues: * **MCP Server:** 媒体控制平台服务器 (Méitǐ Kòngzhì Píngtái Fúwùqì) * **Agent Flow:** 代理流程 (Dàilǐ Liúchéng) * **Team of Experts:** 专家团队 (Zhuānjiā Tuánduì) * **Skill-Based Routing:** 基于技能的路由 (Jīyú Jìnéng de Lùyóu) * **Presence-Based Routing:** 基于状态的路由 (Jīyú Zhuàngtài de Lùyóu) * **Escalation:** 升级 (Shēngjí) * **Transfer:** 转接 (Zhuǎnjiē) * **Collaboration:** 协作 (Xiézuò) * **Knowledge Base:** 知识库 (Zhīshì Kù) * **IVR (Interactive Voice Response):** 交互式语音应答 (Jiāohùshì Yǔyīn Yìngdá) * **Queue:** 队列 (Duìliè) * **Routing Rules:** 路由规则 (Lùyóu Guīzé) * **Agent Desktop:** 代理桌面 (Dàilǐ Zhuōmiàn) **Important Considerations** * **MCP Server Capabilities:** The specific features and capabilities of your MCP server will determine which methods are possible. Consult your MCP server documentation or vendor for details. * **Integration:** Integration with other systems (e.g., IVR, CRM, knowledge base) is crucial for many of these methods. * **Agent Training:** Ensure that agents are properly trained on how to use the new features and processes. * **Monitoring and Optimization:** Monitor the performance of the system and make adjustments as needed to optimize routing and efficiency. To give you more specific advice, please provide more details about your MCP server and the specific requirements of your agent flow. For example: * What is the name of your MCP server? * What features does it support (e.g., skill-based routing, presence management, API integration)? * What type of interactions are you handling (e.g., calls, chats, emails)? * What are the specific skills of your experts?

fuel-prices-mcp

MCP server for UK fuel prices, enabling queries for cheapest stations, nearby forecourts, and area price summaries using official government open data.

web-ai-mcp

Provides free access to AI models (GPT-4o mini, Claude 3 Haiku, Llama 3.1) via DuckDuckGo AI chat without login, using stealth browser automation.

Soma MCP Server

Enables running code against tests in an isolated sandbox to obtain PASS/FAIL verdicts with signed, offline-checkable certificates, and generating verified code with attached certificates after execution against derived tests.

aris-md/mcp

A minimal, well-structured MCP server implementation for learning and experimentation that exposes three tools: web search, API search, and client ID processing. It demonstrates clean separation between tool, transport, and LLM layers while supporting multiple AI clients through the Model Context Protocol standard.

MCP Server

A Multi-Agent Conversation Protocol Server that interfaces with the Exa Search API, allowing agents to perform semantic search operations through a standardized protocol.

mcp-watermelon

MCP server for Watermelon.ai that exposes all 13 public API endpoints as tools, enabling AI assistants to manage contacts, conversations, messages, custom fields, and webhooks.

LeetCode MCP (Model Context Protocol)

Okay, I understand. You want to use an MCP (presumably referring to a "Minecraft Protocol" server, though the connection to LeetCode is unclear) to generate LeetCode notes. This is a bit of an unusual request, and I need to make some assumptions to provide a helpful translation. Here's the breakdown and possible interpretations, along with translations: **Understanding the Request (and Assumptions):** * **"MCP Server":** I'm assuming you're *not* actually talking about a Minecraft server. It's more likely you're using "MCP" as shorthand for some kind of **"Machine Comprehension Program"** or a similar AI-powered system. This makes more sense in the context of generating notes. If you *are* talking about a Minecraft server, please clarify how you intend to use it for LeetCode notes! * **"Generate Leetcode Notes":** You want to automatically create notes, summaries, or explanations for LeetCode problems. This could involve: * Summarizing problem statements. * Generating code solutions (in various languages). * Explaining the logic behind solutions. * Creating test cases. * Providing time and space complexity analysis. **Possible Scenarios and Translations:** Based on the assumption that "MCP Server" refers to an AI-powered system, here are a few ways to phrase your request in Chinese, depending on the specific nuance you want to convey: **Scenario 1: General Request (Using an AI system to create LeetCode notes):** * **Chinese:** 使用机器学习系统生成 LeetCode 笔记 (Shǐyòng jīqì xuéxí xìtǒng shēngchéng LeetCode bǐjì) * **Literal Translation:** Use a machine learning system to generate LeetCode notes. * **Explanation:** This is a broad and general translation. It assumes the "MCP Server" is a machine learning system. **Scenario 2: More Specific (Using a server-based AI to generate LeetCode notes):** * **Chinese:** 使用服务器端的 AI 系统生成 LeetCode 笔记 (Shǐyòng fúwùqì duān de AI xìtǒng shēngchéng LeetCode bǐjì) * **Literal Translation:** Use a server-side AI system to generate LeetCode notes. * **Explanation:** This emphasizes that the AI is running on a server. **Scenario 3: Focusing on Automation (Automated generation of LeetCode notes):** * **Chinese:** 自动化生成 LeetCode 笔记 (Zìdòng huà shēngchéng LeetCode bǐjì) * **Literal Translation:** Automatically generate LeetCode notes. * **Explanation:** This focuses on the automated aspect, without explicitly mentioning the AI system. It implies that some system is doing the generation. **Scenario 4: If you *really* meant Minecraft (highly unlikely, but just in case):** * **Chinese:** 使用 Minecraft 服务器生成 LeetCode 笔记 (Shǐyòng Minecraft fúwùqì shēngchéng LeetCode bǐjì) * **Literal Translation:** Use a Minecraft server to generate LeetCode notes. * **Explanation:** This is the literal translation if you meant a Minecraft server. It's highly improbable that this is what you meant, as the connection is unclear. You would need to explain *how* you intend to use a Minecraft server for this. Perhaps you're thinking of using command blocks or a mod to create a visual representation of algorithms? **Key Vocabulary:** * **LeetCode:** LeetCode (No translation needed, it's a proper noun) * **笔记 (bǐjì):** Notes * **生成 (shēngchéng):** To generate, to produce * **机器学习 (jīqì xuéxí):** Machine learning * **人工智能 (réngōng zhìnéng) / AI:** Artificial intelligence / AI * **服务器 (fúwùqì):** Server * **自动化 (zìdòng huà):** Automation, automated **To get a more accurate translation, please provide more context:** * **What is the "MCP Server" you are referring to?** Is it a specific software, a type of AI, or something else? * **What kind of notes do you want to generate?** Summaries, code solutions, explanations, test cases, etc.? * **What is the purpose of generating these notes?** Studying, sharing, etc.? The more information you give me, the better I can tailor the translation to your specific needs.

pyMSO5000 MCP Server

Enables AI agents to control Rigol MSO5000 oscilloscopes through VISA, including acquisition, channels, trigger, timebase, waveform generator, display, and front-panel controls, with risk-based permission gating for direct SCPI operations.

rocket-cli

Rocket.Chat bridge with a local SQLite/FTS5 cache — CLI for humans, MCP server for LLM agents.

OpenFeature MCP Server

Provides OpenFeature SDK installation guidance for various programming languages and enables feature flag evaluation through the OpenFeature Remote Evaluation Protocol (OFREP). Supports multiple AI clients and can connect to any OFREP-compatible feature flag service.