"A service for finding coding review resources and best practices" matching MCP servers:

A production-ready generic FastMCP server template with SQLAlchemy async CRUD, enabling rapid bootstrapping of MCP data-management services. It provides registry-driven CRUD, FK resolution, conflict versioning, and multiple transports.

Enables static, database-free SQL health checks that return rule-based findings and verdicts, propose executable fixes, and verify rewrites are equivalent while comparing execution plans and suggesting indexes. Supports batch/file/git-diff review for CI gating, all at zero-dependency Tier0.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Provides MySQL database query capabilities through MCP protocol, enabling AI assistants to retrieve table metadata, execute SQL queries, and manage database interactions via Resources, Prompts, and Tools.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Enables an engineering assistant to persist and query local CAD review context—named features, notes, tags, and revision-bound decisions with their requirements and evidence—in SQLite by artifact, entity, text, or tag, marking records stale against a caller-supplied revision. It never opens the CAD file, so it works on a laptop with no CAD software or other server running.

Exposes data query and auto-insights (anomaly detection) as MCP tools. Enables AI agents to query metrics, list columns, and get data insights directly from pandas.

Enables users to access a local ephemeris database of 111 Chinese remote-sensing satellites, including catalog data, TLE history, sensors, and transit windows, via Streamable HTTP for SIRIAgent.

An MCP server that enables Claude to execute SQL queries on MySQL databases with automatic connection management and error handling.

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

A Model Context Protocol server that enables Claude to execute SQL queries on Snowflake databases with automatic connection lifecycle management.

Enables natural-language queries over data warehouses with catalog-grounded semantics and per-query authorization, returning answers with attached reasoning.

Enables reviewing BigQuery SQL queries for performance issues, cost estimation, and suggested rewrites via an MCP interface.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Oracle Service Cloud (beta): https://www.cdata.com/download/download.aspx?sku=KOZK-V&type=beta

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Jira Service Management (beta): https://www.cdata.com/download/download.aspx?sku=GKZK-V&type=beta

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 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 interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

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

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

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 operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.

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.

Enables LLMs and MCP clients to discover and use generated CRUD services through MCP tools and resources, exposing actions like create, update, delete, and read-only list/get access alongside REST endpoints.

Enables AI assistants to discover and invoke generated CRUD tools and read-only resources, letting them interact directly with REST-backed services built on Express, Mongoose, or Sequelize.

Enables LLMs and AI assistants to discover and use tools and resources for CRUD operations on generated services, providing direct interaction with the same data exposed by REST endpoints.

Enables LLMs to discover and invoke CRUD tools and read-only resources for generated services, allowing direct interaction with the same data exposed by the REST API.

Enables LLMs to interact with generated REST API services by exposing MCP tools and resources for CRUD operations, listing, and retrieval. It lets AI clients discover and call create, update, delete, list, and get-by-id actions against the same data available over REST.