Unlock the Power of AI: A Guide to Model Context Protocol Servers
Want to give Large Language Models (LLMs) secure and controlled access to tools and data? This guide explores the world of Model Context Protocol (MCP) servers, providing insight into reference implementations, community-built servers, and essential resources. Discover how MCP servers are revolutionizing AI integration and security, empowering you to build smarter, more versatile applications.
What are Model Context Protocol Servers?
Model Context Protocol (MCP) servers are crucial for connecting Large Language Models (LLMs) to a variety of tools and data sources. These servers act as intermediaries, ensuring LLMs have secure and controlled access while expanding their capabilities. Using an MCP server allows you to connect services like databases, search engines, and internal application program interfaces so that your LLM can gather the information to fulfill complex tasks.
Why Use Model Context Protocol Servers?
- Enhanced Security: MCP provides a secure gateway for LLMs to access external resources.
- Controlled Access: Configure granular permissions, ensuring data privacy and preventing misuse.
- Versatile Integration: Connect LLMs to diverse tools and data sources.
Explore Reference MCP Servers
These servers illustrate MCP features and SDKs in TypeScript and Python, serving as excellent starting points for understanding and implementing MCP.
- AWS KB Retrieval: Retrieve information from AWS Knowledge Base using Bedrock Agent Runtime.
- Brave Search: Conduct web and local searches using Brave's Search API.
- EverArt: Generate AI images using various models.
- Everything: A comprehensive test server with prompts, resources, and tools
- Fetch: Efficiently fetch and convert web content for LLM usage.
- Filesystem: Conduct secure file operations with configurable access controls.
- Git: Read, search, and manipulate Git repositories.
- GitHub: Manage repositories, perform file operations, and integrate with the GitHub API.
- GitLab: Leverage the GitLab API for project management.
- Google Drive: Access and search files within Google Drive.
- Google Maps: Utilize location services, directions, and place details.
- Memory: Build a knowledge graph-based persistent memory system.
- PostgreSQL: Enable read-only database access with schema inspection.
- Puppeteer: Automate browser interactions and web scraping.
- Sentry: Retrieve and analyze issues from Sentry.io, the application performance monitoring platform.
- Sequential Thinking: Facilitate dynamic and reflective problem-solving through thought sequences.
- Slack: Manage channels and messaging within Slack.
- Sqlite: Interact with databases for business intelligence.
- Time: Access time and timezone conversion capabilities.
Discover Third-Party MCP Servers
Explore production-ready MCP servers built and maintained by various companies, officially integrated to enhance their platforms.
- Apify: Extract data from websites and more using pre-built cloud tools.
- Axiom: Query and analyze logs, traces, and event data using natural language.
- Browserbase: Automate browser interactions in the cloud.
- Cloudflare: Deploy and configure resources on the Cloudflare developer platform.
- E2B: Run code in secure sandboxes.
- eSignatures: Manage contracts and templates for drafting, reviewing, and sending.
- Exa: Utilize a search engine designed for AIs.
- Fireproof: Use an immutable ledger database with live synchronization.
- Grafana: Search dashboards, investigate incidents, and query data sources.
- IBM wxflows: Build, test, and deploy tools for any data source.
- Integration App: Interact with SaaS applications on behalf of customers.
- JetBrains: Work on code using JetBrains IDEs.
- Kagi Search: Search the web using Kagi's search API.
- Meilisearch: Interact and query with Meilisearch's full-text and semantic search API.
- Metoro: Interact with Kubernetes environments monitored by Metoro.
- MotherDuck: Analyze data with MotherDuck and local DuckDB.
- Needle: Implement production-ready RAG for document search and retrieval.
- Neo4j: Utilize a graph database server with schema and read/write capabilities.
- Neon: Interact with the Neon serverless Postgres platform.
- Oxylabs: Scrape websites with Oxylabs Web API, supporting dynamic rendering and parsing.
- Qdrant: Implement a semantic memory layer on top of the Qdrant vector search engine.
- Raygun: Interact with crash reporting and real user monitoring data on your Raygun account.
- Riza: Use an arbitrary code execution and tool-use platform.
Resources
Get Started with MCP Servers Today
By leveraging Model Context Protocol servers, you can enhance the capabilities of LLMs with secure access to external resources. Whether you choose pre-built third-party integrations or build your custom solutions using reference servers and SDKs, the possibilities are endless. Start exploring MCP servers and transform your AI applications today.