"A server for detecting and analyzing intent" matching MCP servers:

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

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

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

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

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.

Exposes every generated Express service to LLM clients over HTTP as MCP tools (create, update, delete actions) and resources (list and get-by-id context), so AI assistants can discover and manipulate application data without raw HTTP calls. This lets teams run a single codebase that serves both traditional REST clients and AI agents such as Cursor or Claude.

Enables LLMs to interact with generated CRUD services through MCP tools and resources, so they can create, update, list, and fetch records via a standard protocol. It also provides REST API access from the same codebase for traditional clients.

Enables LLM clients such as Claude, ChatGPT, and Cursor to discover and act on generated CRUD services over HTTP through tools like create, update, list, and delete, plus read-only resources for listing and fetching records by ID, with no extra glue code.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

Enables LLMs to discover and invoke generated API operations as MCP tools and resources, supporting create, update, list, and get-by-id actions over the same data exposed by the REST API.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

A FastMCP-based server designed for the banking and fintech domains, providing tools for database queries, Git operations, and deployment management. It features a modular architecture with reusable prompt templates and integrated security practices for sensitive data handling.

Enables LLMs to interact directly with generated REST services by discovering and invoking CRUD tools and reading exposed resources for list and get-by-id data.

It enables AI assistants to discover and invoke CRUD operations as MCP tools and read application data through MCP resources, allowing natural-language interaction with the generated backend.

Gives Claude full read/write access to the Indexed FP&A portal's data, enabling everything a person can do manually on the portal through conversation.

It enables LLMs to interact with generated REST APIs by exposing CRUD operations as MCP tools and readable records as MCP resources. This lets AI clients discover and manage API data through the Model Context Protocol.

Enables LLMs to discover and invoke CRUD operations and read-only data resources for generated services through the Model Context Protocol, alongside traditional REST endpoints.

Enables AI applications to run SQL queries and retrieve results from Oracle Database.

Enables MCP clients such as GitHub Copilot, Codex, Claude... to explore a SQL Server 2017+ database read-only: databases, schemas, tables, views, procedures, functions, indexes and dependency graphs, plus filtered, grouped, sampled and paginated queries capped by row limits.

Gives AI clients guarded access to SAP Business One over SAP HANA / MS SQL and the Service Layer OData API. SQL is read-only, enforced on the server; Service Layer is GET-only by default, with opt-in writes that require user approval unless a profile explicitly turns it off.

Enables secure access to Oracle databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly/readwrite/full) and table-level permissions for safe query execution and data management.

Provides access to MySQL databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly, readwrite, full) and table-level permissions using whitelists, blacklists, wildcards, and regex patterns.

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.