20 Best MCP Servers for Developers in 2025
If you build with MCP, you spend a lot of time wiring models to real-world data, scraping content, or connecting code to spreadsheets and PDFs. Not every server is worth the trouble. Some work the first time, then break for no reason. Others keep going, week after week, even when traffic spikes or the APIs behind them change. The gap between "looks promising" and "actually delivers" matters. I’ve lived through broken automation at 2 AM, raced against flaky PDF parsers, and watched a single weather plugin block a team’s release. You can chase hype, or you can follow what works in the field. I collected these projects for people who want their code to hold up in real-world usage—not just in perfect demos.
Puppeteer MCP
Puppeteer MCP gives developers a way to control a Chrome or Chromium browser from anywhere. It turns web pages into programmable objects. You can grab screenshots, scrape content, and fill out forms without touching a mouse. It shines in web automation, visual testing, and scraping sites that need JavaScript to load.
GitHub: https://github.com/puppeteer/puppeteer
Playwright MCP
Playwright MCP builds on the Playwright framework, bringing cross-browser automation to MCP workflows. It can spin up Chromium, Firefox, or WebKit instances on demand. Developers run automated tests, check how sites behave in different browsers, and script complex multi-page journeys. The API feels modern and robust, built for scale.
GitHub: https://github.com/microsoft/playwright
Browserbase MCP
Browserbase MCP lives in the cloud. It lets you launch real browser sessions through an API, run bulk scraping tasks, or capture dynamic pages. No local installation, no infrastructure headaches. For teams handling lots of concurrent page loads, it offers a fast path to scalable browser automation.
GitHub: https://github.com/browserbase/browserbase
Chrome MCP
Chrome MCP connects directly to the Chrome DevTools Protocol. It gives granular control—network requests, DOM inspection, JavaScript execution—inside a live browser tab. Anyone automating debugging, measuring site performance, or needing deep integration with Chrome finds this server precise and responsive.
GitHub: https://github.com/cyrus-and/chrome-remote-interface
Selenium MCP
Selenium MCP integrates the classic Selenium WebDriver with MCP. It supports a range of browsers and programming languages. Developers automate tests, mimic real user actions, and run regression checks on websites. Teams that already use Selenium can hook into MCP’s ecosystem without rewriting their flows.
GitHub: https://github.com/SeleniumHQ/selenium
Pandoc MCP
Pandoc MCP serves as a universal document converter. It reads and writes Markdown, PDF, Word, HTML, and more. Developers batch-convert reports, migrate blog posts, or build publishing workflows. It handles tricky formatting and complex layouts, letting content move freely between formats.
GitHub: https://github.com/jgm/pandoc
Excel MCP
Excel MCP automates spreadsheet processing. You can read, edit, and generate Excel files on the fly. Businesses build reporting tools, import bulk data, or update analytics dashboards. It works as a bridge between code and Excel, turning tedious data tasks into quick scripts.
GitHub: https://github.com/exceljs/exceljs
PDF MCP
PDF MCP specializes in PDF manipulation. It extracts text, merges or splits files, and creates new PDFs from scratch. Teams digitize paperwork, analyze invoices, or build document archives. The server parses structure and content, making large-scale PDF workflows practical.
GitHub: https://github.com/foliojs/pdfkit
Filesystem MCP
Filesystem MCP offers direct file management. It reads, writes, and organizes files and folders across local or cloud storage. Developers sync data, automate backups, or let applications upload and download assets. With remote access, file operations become as simple as sending an API call.
GitHub: https://github.com/tschaub/mock-fs
Fetch MCP
Fetch MCP acts as a remote HTTP client. It sends API requests, grabs data from third-party services, and passes results back to AI agents or scripts. Use it to reach RESTful endpoints, attach custom headers, and automate data collection from the wider web.
GitHub: https://github.com/node-fetch/node-fetch
Apidog MCP
Apidog MCP focuses on API development and testing. It mocks endpoints, generates test cases, and keeps API documentation up to date. Developers simulate edge cases, automate checks, or share working examples. It’s a toolbox for anyone building or refining APIs.
GitHub: https://github.com/apidog/apidog-openapi
GitHub MCP
GitHub MCP hooks MCP servers into the GitHub platform. It pulls code, files issues, manages pull requests, and tracks repository activity. Teams automate open-source workflows, review contributions, or trigger builds without manual intervention.
GitHub: https://github.com/octokit/octokit.js
Jupyter MCP
Jupyter MCP brings interactive notebooks to the MCP world. It runs code cells, generates charts, and returns data analysis results on demand. Data scientists automate reporting, build dashboards, or share reproducible experiments—without leaving their toolchain.
GitHub: https://github.com/jupyter/notebook
Weather MCP
Weather MCP provides up-to-date weather information as an API. It taps into meteorological data sources, offering current conditions, forecasts, and climate stats. Apps use it to display local weather, trigger alerts, or plan logistics based on real-time updates.
GitHub: https://github.com/robertoduessmann/weather-api
Claude MCP
Claude MCP connects Anthropic’s Claude model to applications via MCP. It enables conversational AI, task automation, and text generation at scale. Developers script dialogue agents, summarize content, or build assistants powered by Claude’s large language capabilities.
GitHub: https://github.com/anthropics/anthropic-sdk-python
Anthropic MCP
Anthropic MCP integrates a suite of Anthropic’s AI services under one roof. It supports multiple models, with a focus on privacy and security. Enterprises use it to handle sensitive data, automate support, or build custom AI workflows in a controlled environment.
GitHub: https://github.com/anthropics/anthropic-sdk-python
OpenAI MCP
OpenAI MCP serves as a gateway to OpenAI’s models, including ChatGPT and GPT-4. Applications generate text, analyze language, or automate content pipelines. The MCP server translates requests into OpenAI API calls, handling everything from chatbot queries to advanced document processing.
GitHub: https://github.com/openai/openai-python
Sequential Thinking MCP
Sequential Thinking MCP helps applications break down and execute multi-step tasks. It orchestrates workflows, chaining operations and passing results between steps. Developers build pipelines where decisions depend on previous outputs, creating more adaptive and capable AI systems.
GitHub: https://github.com/langchain-ai/langchain
Memory MCP
Memory MCP manages context and persistent state for AI interactions. It stores conversation history, facts, or session data, letting applications “remember” across requests. Use cases include personal assistants, customer support bots, or any tool that benefits from long-term memory.
GitHub: https://github.com/langchain-ai/langchain
ScaleMCP
ScaleMCP handles orchestration and scaling for MCP workloads. It distributes tasks, manages clusters, and ensures high availability in busy deployments. Teams with large or fluctuating demands use it to keep response times low and systems running smoothly.
GitHub: https://github.com/scaleai/scaleapi-python-client
MCP Bridge
MCP Bridge acts as a translator between MCP and other protocols. It routes RESTful requests, adapts formats, and enables integration with third-party tools. Companies link diverse systems through a single entry point, streamlining complex tech stacks.
GitHub: https://github.com/robusta-dev/bridge
MCP Gateway
MCP Gateway focuses on secure, enterprise-grade access. It enforces policies, manages authentication, and monitors traffic. Organizations deploy it to control how MCP servers interact with sensitive data or internal systems.
GitHub: https://github.com/ory/oathkeeper
wong2/awesome-mcp-servers
wong2/awesome-mcp-servers is a curated list, not a server itself. It collects MCP server projects, tools, and documentation from around the web. Developers use it to discover new tools, compare solutions, and find code examples.
GitHub: https://github.com/wong2/awesome-mcp-servers
Dynamic MCP
Dynamic MCP supports live scaling and hot-swapping of resources. It adds or removes compute power as needed, letting workloads flex to demand. Environments with unpredictable traffic use it to keep performance steady without overprovisioning.
GitHub: https://github.com/Netflix/dynomite
MCP RESTful Proxy
MCP RESTful Proxy provides a simple API layer that sits between MCP servers and other services. It standardizes communication, making it easier to connect disparate systems. Teams use it to bridge legacy tools, cloud apps, and custom workflows.
GitHub: https://github.com/http-party/node-http-proxy
MCP File Converter
MCP File Converter handles document and media format conversion. It turns one file type into another—Word to PDF, JPEG to PNG, and beyond. Batch processing and broad compatibility make it a staple for data migration and content pipelines.
GitHub: https://github.com/transcode-open/aptly
MCP PDF Parser
MCP PDF Parser digs into PDFs to extract structure and content. It pulls out tables, text, and images, transforming documents into usable data. Businesses rely on it for invoice scanning, contract review, and automated archiving at scale.
GitHub: https://github.com/pdfminer/pdfminer.six
You don’t see all the sharp edges of MCP in polished launch posts or vendor decks. But when a job matters—when hundreds of daily processes hinge on a script running reliably—these servers show their value. The right tools quietly become part of your routine. The best ones keep working even when nobody is watching.