"Methods for Saving, Reading, and Querying Data" matching MCP servers:

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A semantic layer query engine with MCP support, enabling AI assistants to query structured data through natural language and declarative interfaces.

A proof of concept MCP server for Apache OFBiz

Enables loading CSV text, filtering and aggregating datasets over Streamable HTTP, and optionally using Amazon Bedrock to turn query results into concise answers suitable for speech.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.

Enables Claude to answer plain-English questions by listing and describing database tables, running read-only SQL queries, and searching a folder of policy documents.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Enables natural language querying of PostgreSQL via MCP, combining SQL, vector search, and knowledge graph with automatic routing and token-aware curation.

Enables querying and analyzing user, product, and order data with filtering capabilities and real-time statistics. Supports WebSocket connections to XiaoZhi AI platform with automatic reconnection.

Automatically routes natural language questions to RAG or Text2SQL paths to answer queries about virtual construction site data, supporting semantic search and structured aggregation.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

Secure Edge Gateway for Data Normalization.

Enables SQL agents to connect to any SQLAlchemy-supported database via MCP, providing read-only SQL querying, automatic table summarization, and column content search.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

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 Salesforce Data Cloud (beta): https://www.cdata.com/download/download.aspx?sku=LRZK-V&type=beta