"How to use Figma" matching MCP servers:

Enables Claude Desktop and other AI tools to interact directly with Figma, allowing for powerful AI-assisted design capabilities through natural language commands.

Enables Cursor to access Figma files through the Model Context Protocol, enhancing its ability to accurately interpret and utilize design data for code generation.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

Cross-model AI memory persistence server that gives every AI tool you use access to the same persistent memory.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Advanced content gap analysis using Query Decomposition and Keyword Fan-Out (Google's patented methodology). Tells you exactly what user queries your content covers - and what it misses. Built on academic research because I needed to understand how AI search engines actually evaluate content.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

A ready-to-use starter implementation of the Model Context Protocol (MCP) server that enables applications to provide standardized context for LLMs with sample resources, tools, and prompts.

Lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things with Neon.

Provides a 'think' tool that allows Claude and other LLMs to add dedicated thinking steps during complex tool use scenarios, creating space for structured reasoning and improving problem-solving capabilities.

Enables AI applications to use advanced memory management capabilities through the memU AI framework. Supports storing conversation memories, semantic retrieval, multi-user management, and memory statistics via standardized MCP protocol.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables AI assistants to use Cohere's language models, embeddings, and reranking capabilities via the Model Context Protocol.

Enables Claude to index and retrieve context from codebases using self-hosted Milvus for semantic search, with hardened reliability and security for production use.

Enables Pi to use GZMO's curated memory system, providing tools for memory status, search, recall, and chain operations via MCP.

Enables AI agents to get read-only trust verdicts on knowledge records by evaluating evidence maturity, provenance, intended use, risk level, and scope before deciding whether knowledge may be used.

Enables agents to perform semantic search, text comparison, clustering, and zero-shot classification locally without API costs, allowing repeated in-loop use.