"Allowing MCP and Claude to Interact with Firebase/Firestore Database" 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.

A Model Context Protocol server that enables LLMs like Claude to interact with SQLite and SQL Server databases, allowing for schema inspection and SQL query execution.

MCP server for Microsoft SQL Server that lets LLMs explore schema and execute read-only SELECT queries, with optional stored procedure execution when explicitly enabled.

A Model Context Protocol server that enables LLMs to interact with databases (currently MongoDB) through natural language, supporting operations like querying, inserting, deleting documents, and running aggregation pipelines.

An MCP server that provides deterministic math computation (numeric, symbolic, unit, matrix) and hybrid retrieval over study notes/textbooks with citations, helping Claude become a reliable study partner.

Enables Claude to query and manage databases (SQLite, SQL Server, PostgreSQL, MySQL) through natural language, supporting read/write operations and schema management.

Enables Claude to connect to and interact with SQLite, SQL Server, PostgreSQL, and MySQL databases through natural language. Supports executing queries, managing tables, exporting data, and storing business insights with authentication options including AWS IAM.

Provides universal database operations for AI assistants through MCP, supporting 40+ databases including PostgreSQL, MySQL, MongoDB, Redis, and SQLite with built-in introspection tools for schema exploration.

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.

A persistent semantic memory system for Claude Code that provides a structured, versioned document store with semantic search and graph visualization. It acts as a memoization layer to store and retrieve research, design decisions, and codebase insights across different work sessions.

Enables GitHub Copilot and other LLMs to execute read-only SQL queries against Oracle databases with secure connection pooling and schema introspection capabilities.

Multi-agent AI consultation framework for Claude Code via MCP — get second opinions from OpenAI, Gemini, Qwen, DeepSeek

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.

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

Enables Claude Code to retain persistent cross-session memory with semantic search, automatically tracking user corrections as behavioral patterns that move through lifecycle stages. It also extracts signals from every session to evolve and promote behavioral frameworks, giving the assistant developing judgment over time.

Enables Claude Code sessions to persist identity and cross-session memory through a local SQLite store with semantic search, so past facts, decisions, and lessons can be recalled by meaning. It also detects and classifies user corrections into behavioral patterns that progress from new to internalized, letting reflection cycles evolve skills that work over time.

Enables Claude Code to retain cross-session memory of facts, decisions, and lessons with semantic search, while tracking user corrections as behavioral patterns and evolving self-improving frameworks over time. All processing runs locally through an MCP server and hooks, requiring no cloud service or API key.

Enables structured team communication for Claude Code agents through Slack-like channels and direct messages. Supports project isolation, subscription management, and agent notes for sophisticated multi-agent collaboration workflows.

Enables Claude to search past coding transcripts stored locally — by exact words or by meaning — read them page by page, and reopen them in a terminal to resume work in the original directory. Everything stays on the machine, with a year-long archive.

Gives Claude Code persistent memory across sessions with semantic search, tracks and classifies user corrections to surface behavioral patterns, and evolves behavioral frameworks over time based on accumulated evidence. Runs entirely locally through 15 MCP tools and hooks, requiring no API key or cloud service.