Top MCP Servers

Provides integration with KubeSphere APIs, exposing workspace management, cluster management, user and role handling, and extensions through Model Context Protocol.

Enables MCP clients to perform full‑stack GitHub repository operations—issues, pull requests, branches, files, collaborators, and more—using only a personal access token, without Docker or external CLI tools.

Enables AI assistants and MCP clients to manage tasks, projects, areas, and tags in Things3 on macOS via a set of 25 specialized tools, providing automatic tag creation, error correction, and bulk operations.

Retrieve Bilibili user profiles, video details, and perform keyword video searches via an MCP server.

Provides a Model Context Protocol server that connects to the Databricks Genie API, enabling large language models to ask natural language questions, execute SQL queries, and interact with Genie conversational agents.

Integrate AI agents with Chargebee to automate billing and subscription workflows using AgentKit.

Generate editable CAD parts or assemblies directly from natural‑language prompts by leveraging gNucleus generative AI models through a lightweight MCP server.

Provides a standardized interface for running powerful LLM system optimizations, evaluations, and experiments via the Model Context Protocol.

Provides a Python wrapper for ServiceNow APIs and can operate as an MCP server, enabling programmatic interaction with ServiceNow tables, incidents, change management, CI/CD, and custom endpoints.

Provides a streamlined foundation for building Model Context Protocol (MCP) servers in Python, facilitating AI‑assisted development of MCP tools.

Enables AI assistants to execute Apex code, run SOQL/SOSL queries, manage metadata, and automate development workflows within Salesforce orgs via the Salesforce CLI.

Packages GDAL‑style geospatial workflows with Python‑native libraries (Rasterio, GeoPandas, PyProj, etc.) and adds AI‑agent‑driven catalog discovery, metadata intelligence, and raster/vector processing backed by epistemic reasoning.

Scalable multi‑language code analysis framework built on Tree‑sitter, operable through a command‑line interface or as an MCP server for AI assistants.

Provides persistent memory, semantic code search, and graph‑based analysis for AI tools through an MCP server.

Enables generation of PlantUML diagrams through a Model Context Protocol (MCP) server, returning embeddable SVG/PNG URLs and optional local file saving.

Provides access to Aiven PostgreSQL, Kafka, ClickHouse, Valkey, and OpenSearch services via Model Context Protocol, enabling LLMs to interact with Aiven resources for full‑stack solutions.

Provides a scalable platform for dynamic tool registration and execution based on API definitions, integrating services like Slack, Notion, Claude.ai, and Cursor.ai, with flexible authentication and comprehensive logging.

Decompiles Java .class files, package names, and JAR archives into readable source code through an MCP‑compatible server.

Enables AI tools to explore and manipulate kintone data through the Model Context Protocol.

Pins third‑party dependencies—Docker base images and GitHub Actions—to immutable digests, ensuring reproducible builds and protecting against supply‑chain attacks.

Enables AI assistants to control iTerm2 terminals via Model Context Protocol, offering session creation, command execution, output retrieval, listing, and termination of terminal instances.

Enables AI tools and agents to interact with Cashfree payment, payouts, and SecureID services through the Model Context Protocol.

Enables AI agents to create, execute, and analyze Conductor workflows through an MCP server that reads a simple JSON configuration.

Provides detailed geolocation information for IPv4 and IPv6 addresses using the IP2Location.io API.

Aggregates web data via Tavily's Search and Crawl APIs, structures the results for LLM-friendly markdown generation.

Provides a secure bridge for AI assistants to query and analyze YNAB budgeting data via the Model Context Protocol.

Generate PowerPoint presentations programmatically via an MCP server, enabling automated report and slide‑deck creation.

Provides recent NBA game scores, player statistics, and advanced metrics to Claude via the MCP protocol.

Provides a bridge between LLM applications and the Unleash feature flag system, enabling AI apps to check, create, update, and list feature flags via the Model Context Protocol.

Provides tools to interact with the Linear issue‑tracking system via the MCP protocol, enabling creation, updating, searching, commenting on issues, and retrieving team information while respecting API rate limits.

Provides control and access to a video surveillance system, allowing retrieval of live and recorded video streams, channel status queries, PTZ camera positioning, and playback dialog management.

Generate custom AI‑powered memes and convert them into Telegram or WhatsApp stickers without requiring external APIs.