Discover Awesome MCP Servers
Extend your agent with 57,688 capabilities via MCP servers.
- All57,688
- Developer Tools3,867
- Search1,714
- Research & Data1,557
- AI Integration Systems229
- Cloud Platforms219
- Data & App Analysis181
- Database Interaction177
- Remote Shell Execution165
- Browser Automation147
- Databases145
- Communication137
- AI Content Generation127
- OS Automation120
- Programming Docs Access109
- Content Fetching108
- Note Taking97
- File Systems96
- Version Control93
- Finance91
- Knowledge & Memory90
- Monitoring79
- Security71
- Image & Video Processing69
- Digital Note Management66
- AI Memory Systems62
- Advanced AI Reasoning59
- Git Management Tools58
- Cloud Storage51
- Entertainment & Media43
- Virtualization42
- Location Services35
- Web Automation & Stealth32
- Media Content Processing32
- Calendar Management26
- Ecommerce & Retail18
- Speech Processing18
- Customer Data Platforms16
- Travel & Transportation14
- Education & Learning Tools13
- Home Automation & IoT13
- Web Search Integration12
- Health & Wellness10
- Customer Support10
- Marketing9
- Games & Gamification8
- Google Cloud Integrations7
- Art & Culture4
- Language Translation3
- Legal & Compliance2
Browser MCP Server
Enables AI assistants to automate web browsers through Playwright, providing capabilities for navigation, content extraction, form filling, screenshot capture, and JavaScript execution. Supports multiple browser engines with comprehensive error handling and security features.
Verilex Data
Query 20 structured datasets from AI agents — healthcare providers (9M NPI records), SEC EDGAR filings, PACER federal courts, USPTO patents and trademarks, OFAC sanctions screening, crypto whale wallets, DeFi liquidation signals, Polymarket smart money, economic indicators (FRED/BLS), federal contracts, NOAA weather, and OTC shell risk scoring. Pay per query, no subscriptions
Writespace
Persistent docs and memory for AI agents. Writespace is a collaborative markdown editor with a built-in MCP server — your model reads, writes, organizes, and searches a shared workspace while humans edit the same docs live. Drop the ranked full-text search straight in as RAG retrieval.
Avalara AvaTax MCP Server by CData
This read-only MCP Server allows you to connect to Avalara AvaTax data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp
AI Image Analysis MCP
Provides AI-powered image analysis using Google Gemini 2.0 Flash, with support for multiple access methods and robust security features.
ltm
Portable memory protocol for AI coding sessions. Push the state of a session (goal, decisions, attempts, next step) from one MCP-capable agent and pull it back from another.
neuromcp
Semantic memory for AI agents — local-first MCP server with hybrid search, knowledge graph, contradiction detection, and plan-then-commit consolidation.
mcp-personal
MCP server that provides tools to manage Gmail and Outlook emails, and search Mercadona products, for use with Cursor and LangChain.
Premiere MCP 剪辑助手
该MCP服务器使AI助手(如Claude Code、Codex)能够通过桥接目录和CEP面板与Adobe Premiere Pro交互,支持素材扫描、编辑规划、粗剪执行等操作,强调先规划后执行和人工复核。
Handaas Qualification MCP Server
Provides comprehensive enterprise qualification and certificate data, including honors, administrative licenses, and professional background statistics. It enables users to search for companies and verify their bidding eligibility or compliance status through natural language queries.
聚义厅MCP
An AI personality collaboration tool based on Model Context Protocol (MCP) that enables users to summon and collaborate with multiple AI personas for intelligent analysis and problem-solving.
LinkedIn MCP
Enables AI assistants to access and interact with LinkedIn data—profiles, messaging, jobs, companies, and more—via MCP, with remote or local deployment.
Local Scanner MCP Server
Here are a few options for an MCP (Malware Configuration Parser) server that can scan local code and localhost URLs, along with considerations for each: **1. Using Existing Malware Analysis Sandboxes (with API access):** * **Concept:** Leverage established online sandboxes that offer API access. You'd submit your local code or URLs to the sandbox via its API, and it would perform the analysis and return the results. This is often the most practical approach because it avoids the complexity of setting up and maintaining your own full-fledged sandbox. * **Examples:** * **VirusTotal:** A very popular and free (with limitations) service. It aggregates results from many different antivirus engines. Excellent for a quick check. The API has rate limits, so it's not ideal for high-volume scanning without a paid subscription. * **Hybrid Analysis (Falcon Sandbox):** A more advanced sandbox that provides detailed behavioral analysis reports. It has a free tier with limitations and paid options for more features and higher usage. * **ANY.RUN:** An interactive online sandbox that allows you to observe malware execution in real-time. It has a free tier and paid options. * **Joe Sandbox Cloud:** A commercial sandbox with a wide range of analysis capabilities. * **Implementation:** 1. **Choose a Sandbox:** Select a sandbox that meets your needs in terms of features, pricing, and API access. 2. **Obtain API Key:** Register for an account and obtain an API key. 3. **Write a Script/Application:** Develop a script (e.g., in Python) or application that: * Reads the local code or URL. * Uses the sandbox's API to submit the code/URL for analysis. * Parses the API response to extract the relevant information (e.g., detected malware, behavioral indicators). * Presents the results to the user. * **Pros:** * Relatively easy to set up. * Leverages the expertise and resources of established security vendors. * Access to a wide range of analysis tools and techniques. * Often provides detailed reports. * **Cons:** * Requires an internet connection. * May have rate limits or usage restrictions (especially with free tiers). * You are trusting a third party with your code/URLs (consider privacy implications). * API changes can break your integration. **2. Using Open-Source Malware Analysis Tools (Local Installation):** * **Concept:** Install open-source malware analysis tools on your own server. This gives you more control but requires significantly more effort to set up and maintain. * **Examples:** * **Cuckoo Sandbox:** A popular open-source automated malware analysis system. It runs malware in a virtualized environment and records its behavior. Requires significant setup and configuration. * **YARA:** A pattern-matching tool that can be used to identify malware based on rules. You'll need to create or find YARA rules relevant to the types of malware you're looking for. * **ClamAV:** An open-source antivirus engine. Can be used for basic malware detection. * **Radare2:** A reverse engineering framework that can be used to analyze malware. Very powerful but has a steep learning curve. * **Implementation:** 1. **Choose Tools:** Select the tools that best fit your needs. Cuckoo Sandbox is a good starting point for comprehensive analysis. 2. **Install and Configure:** Follow the installation instructions for each tool. This can be complex, especially for Cuckoo Sandbox. You'll need to set up virtual machines, networking, and other dependencies. 3. **Develop a Script/Application:** Write a script or application that: * Reads the local code or URL. * Submits the code/URL to the analysis tools. * Parses the output of the tools to extract the relevant information. * Presents the results to the user. * **Pros:** * More control over the analysis environment. * No reliance on third-party services. * Can be used offline. * Potentially more privacy. * **Cons:** * Significantly more complex to set up and maintain. * Requires a good understanding of malware analysis techniques. * Requires more resources (hardware, time, expertise). * You are responsible for keeping the tools up-to-date and secure. * May require creating your own malware signatures or rules. **3. Simplified Local Scanning (Basic):** * **Concept:** Use simpler tools for basic scanning, such as file hashing and string searching. This is not a full-fledged MCP server but can be useful for identifying known malicious files or patterns. * **Examples:** * **Hashing:** Calculate the MD5, SHA-1, or SHA-256 hash of the file and compare it to known malware hashes (e.g., from VirusTotal's database). * **String Searching:** Search for suspicious strings in the code, such as URLs, IP addresses, or function names associated with malware. * **Regular Expressions:** Use regular expressions to identify patterns that might indicate malicious code. * **Implementation:** 1. **Write a Script/Application:** Develop a script or application that: * Reads the local code or URL. * Calculates the hash of the file. * Searches for suspicious strings or patterns. * Presents the results to the user. * **Pros:** * Simple to implement. * Fast. * Can be used offline. * **Cons:** * Limited detection capabilities. * Easily bypassed by malware authors. * High false positive rate. **Important Considerations:** * **Security:** If you are running malware analysis tools on your own server, it is crucial to isolate the environment to prevent malware from escaping and infecting your system. Use virtualization, sandboxing, and network segmentation. * **Privacy:** Be careful about submitting sensitive code or URLs to third-party services. Consider the privacy implications and choose services that have a good reputation for data security. * **False Positives:** Malware analysis tools can sometimes produce false positives. It is important to carefully review the results and investigate any suspicious findings. * **Updates:** Keep your malware analysis tools and signature databases up-to-date to ensure that they can detect the latest threats. * **Legal Issues:** Be aware of any legal restrictions on analyzing malware. In some jurisdictions, it may be illegal to possess or analyze malware without authorization. **Example (Python using VirusTotal API - Basic):** ```python import requests import hashlib import os def scan_file_with_virustotal(file_path, api_key): """Scans a file with VirusTotal using its API.""" if not os.path.exists(file_path): print(f"Error: File not found: {file_path}") return try: with open(file_path, "rb") as f: file_content = f.read() file_hash = hashlib.sha256(file_content).hexdigest() url = "https://www.virustotal.com/api/v3/files" headers = {"x-apikey": api_key} files = {"file": (os.path.basename(file_path), file_content)} response = requests.post(url, headers=headers, files=files) if response.status_code == 200: analysis_id = response.json()['data']['id'] print(f"File uploaded. Analysis ID: {analysis_id}") # Poll for results (you might need to wait a few minutes) analysis_url = f"https://www.virustotal.com/api/v3/analyses/{analysis_id}" analysis_response = requests.get(analysis_url, headers=headers) if analysis_response.status_code == 200: analysis_data = analysis_response.json()['data']['attributes']['stats'] print("Analysis Results:") print(f" Detected: {analysis_data['malicious']}") print(f" Undetected: {analysis_data['undetected']}") print(f" Harmless: {analysis_data['harmless']}") print(f" Suspicious: {analysis_data['suspicious']}") else: print(f"Error getting analysis results: {analysis_response.status_code} - {analysis_response.text}") else: print(f"Error uploading file: {response.status_code} - {response.text}") except Exception as e: print(f"An error occurred: {e}") if __name__ == "__main__": file_to_scan = "path/to/your/file.exe" # Replace with the actual path to your file virustotal_api_key = "YOUR_VIRUSTOTAL_API_KEY" # Replace with your VirusTotal API key scan_file_with_virustotal(file_to_scan, virustotal_api_key) ``` **Explanation of the Python example:** 1. **Imports:** Imports necessary libraries (requests for making HTTP requests, hashlib for calculating file hashes, and os for file operations). 2. **`scan_file_with_virustotal` function:** * Takes the file path and VirusTotal API key as input. * Reads the file content in binary mode (`"rb"`). * Calculates the SHA-256 hash of the file. * Constructs the API request to upload the file to VirusTotal. * Sends the request using `requests.post`. * Parses the JSON response to get the analysis ID. * Polls the VirusTotal API to get the analysis results. * Prints the detection statistics (malicious, undetected, harmless, suspicious). * Handles potential errors. 3. **`if __name__ == "__main__":` block:** * Sets the `file_to_scan` and `virustotal_api_key` variables. **You must replace these with your actual file path and API key.** * Calls the `scan_file_with_virustotal` function to scan the file. **To use this example:** 1. **Install `requests`:** `pip install requests` 2. **Get a VirusTotal API Key:** Sign up for a free account on VirusTotal ([https://www.virustotal.com/](https://www.virustotal.com/)) and obtain an API key. 3. **Replace Placeholders:** Replace `"path/to/your/file.exe"` and `"YOUR_VIRUSTOTAL_API_KEY"` with the actual values. 4. **Run the Script:** Execute the Python script. This is a basic example. You can extend it to handle URLs, process the analysis results in more detail, and integrate it into a larger application. Remember to handle errors and rate limits appropriately. **For scanning localhost URLs:** The approach is similar to scanning local files, but instead of reading a file, you would make an HTTP request to the localhost URL and analyze the response. You could use the `requests` library in Python to make the HTTP request and then analyze the HTML or JavaScript code in the response for suspicious patterns. You could also use a headless browser like Puppeteer or Selenium to render the page and analyze the rendered content. Be very careful when visiting localhost URLs, as they could potentially execute malicious code on your system. Choose the option that best suits your needs and technical expertise. For most use cases, using an existing malware analysis sandbox with API access is the most practical and efficient approach. Remember to prioritize security and privacy when handling potentially malicious code.
Google Ads MCP Server
Enables comprehensive Google Ads campaign management and analysis through natural language, including performance metrics, keyword optimization, budget management, and custom GAQL queries.
mcp-bible
MCP server for Bible study, providing multi-version verse lookup, keyword/semantic search, cross-references, and word studies with original language and lexicon details.
Jira Service Management MCP Server
Enables configuration of Jira Service Management Cloud via natural language, supporting request types, custom fields, forms, and more.
ArcRift MCP Server
Persistent memory for AI coding tools that captures conversations, builds a searchable knowledge graph, and automatically injects relevant context into new prompts.
SFCC Development MCP Server
Provides comprehensive access to Salesforce B2C Commerce Cloud development tools including SFCC API documentation, best practices guides, log analysis, and system object definitions. Enables AI assistants to help with SFCC development tasks through both documentation-only mode and full credential-based mode.
markdownlint-mcp
Provides AI assistants with the ability to lint, validate, and auto-fix Markdown files to ensure compliance with established Markdown standards and best practices.
Zohairs-server
Test
Math Operations MCP Server
Enables mathematical operations and calculations through an MCP server interface. Provides computational capabilities accessible via HTTP endpoints for mathematical processing tasks.
Mcp Server Tester
WHOOP MCP Server for Poke
Connects WHOOP fitness data to Poke AI assistant, enabling natural language queries for recovery scores, sleep analysis, strain tracking, and healthspan metrics.
Dear User
Tells you how you and your Claude agent actually work together. Reads CLAUDE.md, hooks, skills, memory + scheduled tasks and writes you a letter. Local-only, no API keys, no data leaves your machine.
Conductor
Provides a persistent hierarchical task tree for LLM agents, enabling them to decompose work, track progress, record results, and handle failures outside the context window, with an optional web UI for monitoring and control.
SkillStrata
Enables automatic discovery and reuse of tools from Claude Code execution traces. Provides MCP tools that are distilled from real work, allowing you to reuse previously written scripts without manual effort.
PixelLabRat
MCP server for generating style-consistent pixel art assets from PixelLab API, with project management, asset review, and an embedded Claude assistant.
ecommerce-mcp
Enables AI to view and manage e-commerce data such as products, orders, and coupons, and perform actions like updating prices, stock, and generating sales reports.
Selenium MCP Server
A server implementation that enables controlling web browsers programmatically through Claude's desktop application, providing comprehensive Selenium WebDriver operations for browser automation with Chrome and Firefox support.
rippr
Extract YouTube transcripts for AI agents, RAG pipelines, and LLM workflows. Supports any YouTube URL. Returns clean text or timestamped segments. No API keys required.