"Cloning, Installing, and Building the Claude Code MCP Repository" matching MCP servers:

Provides persistent memory capabilities for Claude Code using Neo4j graph database to track development tasks, code patterns, solutions, and their relationships across sessions and projects, enabling contextual assistance and pattern recognition.

Enables local Claude Code to interact with Snowflake, Asana, M365, GitHub, and Hive Mind with automatic response truncation to prevent memory overload.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

Read-only MCP server that proxies The Game Pensieve API over Streamable HTTP, letting AI assistants query a personal game collection via tools like search, filters, and summaries. Supports OAuth 2.1 enforcement and owner-scoped access.

A SQL Server CLI and MCP server for Claude Code that supports standard SQL Server authentication for database interaction and management. It enables users to perform schema exploration, execute queries, and manage data records with built-in SQL injection prevention.

Indexes codebases into a SQLite database to provide metadata, exports, dependency graphs, and change tracking for JS/TS projects. It enables users to search for symbols, map internal dependencies, and monitor file changes through MCP tools and a web dashboard.

Enables MCP-compatible LLM clients to interact with IBM Planning Analytics/TM1 models through callable tools, supporting read operations like inspecting cubes, dimensions, and MDX queries, plus write/model-building operations in read/write mode.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

An MCP server that connects Claude to FileMaker databases via the Data API, enabling natural language queries, record management, layout exploration, and script execution.

Enables Claude to interact with FileMaker databases through the FileMaker Data API, supporting multi-database connections, CRUD operations, script execution, and metadata discovery.

TypeScript implementation of the Model Context Protocol that standardizes how LLMs connect to data sources and tools, eliminating vendor lock-in and simplifying AI integration.

An oil & gas data-analytics MCP server that enables guarded SQL queries, well valuation, and map rendering within chat apps.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.