RAG Documentation MCP Server alternatives

1

MCP Local RAG

Privacy-first local semantic document search server for MCP clients.

MCP Local RAG is a privacy-preserving, local document search server designed for use with Model Context Protocol (MCP) clients such as Cursor, Codex, and Claude Code. It enables users to ingest and semantically search local documents without using external APIs or cloud services. All processing, including embedding generation and vector storage, is performed on the user's machine. The tool supports document ingestion, semantic search, file management, file deletion, and system status reporting through MCP.

10 3 MCP

2

Biel.ai MCP Server

Seamlessly connect IDEs to your company’s product documentation using an MCP server.

Biel.ai MCP Server enables AI tools such as Cursor, VS Code, and Claude Desktop to access and utilize a company’s product documentation and knowledge base through the Model Context Protocol. It provides a hosted RAG layer that makes documentation searchable and usable, supporting real-time, context-rich completion and answers for developers. The server can be used as a hosted solution or self-hosted locally or via Docker for advanced customization.

2 2 MCP

3

Trieve

All-in-one solution for search, recommendations, and RAG.

Trieve offers a platform for semantic search, recommendations, and retrieval-augmented generation (RAG). It supports dense vector search, typo-tolerant neural search, sub-sentence highlighting, and integrates with a variety of embedding models. Trieve can be self-hosted and features APIs for context management with LLMs, including Bring Your Own Model and managed RAG endpoints. Full documentation and SDKs are available for streamlined integration.

2,555 229 MCP

4

Driflyte MCP Server

Bridging AI assistants with deep, topic-aware knowledge from web and code sources.

Driflyte MCP Server acts as a bridge between AI-powered assistants and diverse, topic-aware content sources by exposing a Model Context Protocol (MCP) server. It enables retrieval-augmented generation workflows by crawling, indexing, and serving topic-specific documents from web pages and GitHub repositories. The system is extensible, with planned support for additional knowledge sources, and is designed for easy integration with popular AI tools such as ChatGPT, Claude, and VS Code.

9 2 MCP

5

mcp-local-rag

Local RAG server for web search and context injection using Model Context Protocol.

mcp-local-rag is a local server implementing the Model Context Protocol (MCP) to provide retrieval-augmented generation (RAG) capabilities. It performs live web search, extracts relevant context using Google's MediaPipe Text Embedder, and supplies the information to large language models (LLMs) for enhanced, up-to-date responses. The tool is designed for easy local deployment, requiring no external APIs, and is compatible with multiple MCP clients. Security audits are available, and integration is demonstrated across several LLM platforms.

89 18 MCP

6

Context7 MCP

Up-to-date code docs for every AI prompt.

Context7 MCP delivers current, version-specific documentation and code examples directly into large language model prompts. By integrating with model workflows, it ensures responses are accurate and based on the latest source material, reducing outdated and hallucinated code. Users can fetch relevant API documentation and examples by simply adding a directive to their prompts. This allows for more reliable, context-rich answers tailored to real-world programming scenarios.

36,881 1,825 MCP

7

Vectorize MCP Server

MCP server for advanced vector retrieval and text extraction with Vectorize integration.

Vectorize MCP Server is an implementation of the Model Context Protocol (MCP) that integrates with the Vectorize platform to enable advanced vector retrieval and text extraction. It supports seamless installation and integration within development environments such as VS Code. The server is configurable through environment variables or JSON configuration files and is suitable for use in collaborative and individual workflows requiring vector-based context management for models.

97 21 MCP

8

NyxDocs

MCP server for real-time cryptocurrency project documentation and insights.

NyxDocs is a Model Context Protocol (MCP) compatible server built in Python for managing and serving up-to-date documentation for cryptocurrency projects. It aggregates information from multiple sources such as CoinGecko, GitHub, GitBook, Notion, and official websites, providing real-time data and updates on blockchain ecosystems. Featuring tools for searching projects, retrieving detailed info, extracting documentation, and monitoring changes, it is tailored for developers and AI contexts needing access to accurate crypto documentation. The architecture leverages a FastMCP-based server core, automated document scrapers, and supports multi-blockchain environments.

3 3 MCP

9

Raindrop.io MCP Server

Enable LLMs to manage and search Raindrop.io bookmarks via the Model Context Protocol.

Raindrop.io MCP Server is an integration that allows large language models to interact with Raindrop.io bookmarks using the Model Context Protocol. It provides tools to create and search bookmarks, including filtering by tags, and is designed for interoperability with environments like Claude for Desktop. Installation can be done via Smithery or manually, and configuration is managed through environment variables. The project is open source and optimized for secure, tokenized access to Raindrop.io.

63 15 MCP

10

Ragie Model Context Protocol Server

Seamless knowledge base retrieval via Model Context Protocol for enhanced AI context.

Ragie Model Context Protocol Server enables AI models to access and retrieve information from a Ragie-managed knowledge base using the standardized Model Context Protocol (MCP). It provides a retrieve tool with customizable query options and supports integration with tools like Cursor and Claude Desktop. Users can configure API keys, specify partitions, and override tool descriptions. Designed for rapid setup via npx and flexible for project-specific or global usage.

81 18 MCP

11

Vectara MCP Server

Secure RAG server enabling seamless AI integration via Model Context Protocol.

Vectara MCP Server implements the open Model Context Protocol to enable AI systems and agentic applications to connect securely with Vectara's Trusted RAG platform. It supports multiple transport modes, including secure HTTP, Server-Sent Events (SSE), and local STDIO for development. The server provides fast, reliable retrieval-augmented generation (RAG) operations with built-in authentication, rate limiting, and optional CORS configuration. Integration is compatible with Claude Desktop and any other MCP client.

25 8 MCP

12

VictoriaMetrics MCP Server

Model Context Protocol server enabling advanced monitoring and observability for VictoriaMetrics.

VictoriaMetrics MCP Server implements the Model Context Protocol (MCP) to provide seamless integration with VictoriaMetrics, allowing advanced monitoring, data exploration, and observability. It offers access to almost all read-only APIs, as well as embedded documentation for offline usage. The server facilitates comprehensive metric querying, cardinality analysis, alert and rule testing, and automation capabilities for engineers and tools.

87 11 MCP

13

godoc-mcp

Token-efficient Go documentation server for LLMs using Model Context Protocol.

godoc-mcp is a Model Context Protocol (MCP) server that provides efficient, structured access to Go package documentation for large language models. It enables LLMs to understand Go projects without reading entire source files by supplying essential documentation and source code at varying levels of granularity. The tool supports project navigation, automatic module setup, caching, and works offline for both standard and third-party Go packages.

88 11 MCP

14

RAE Model Context Protocol (MCP) Server

An MCP server enabling LLMs to access RAE’s dictionary and linguistic resources.

Provides a Model Context Protocol (MCP) server implementation for the Royal Spanish Academy API, facilitating integration with language models. Offers tools such as search and word information retrieval, exposing RAE’s dictionary and linguistic data to LLMs. Supports multiple transports including stdio and SSE, making it suitable for both direct and server-based LLM interactions.

3 3 MCP

15

In Memoria

Persistent memory and instant context for AI coding assistants, integrated via MCP.

In Memoria is an MCP server that enables AI coding assistants such as Claude or Copilot to retain, recall, and provide context about codebases across sessions. It learns patterns, architecture, and conventions from user code, offering persistent intelligence that eliminates repetitive explanations and generic suggestions. Through the Model Context Protocol, it allows AI tools to perform semantic search, smart file routing, and track project-specific decisions efficiently.

94 17 MCP

16

Code Declaration Lookup MCP Server

Fast, language-agnostic code declaration search and lookup server via MCP.

Provides a Model Context Protocol (MCP) server that indexes code declarations using universal ctags and SQLite with FTS5 full-text search. Offers search and listing functionality for functions, classes, structures, enums, and other code elements across any language supported by ctags. Enables seamless integration with coding agents for dynamic indexing, respects .gitignore, and supports ctags file ingestion and management.

2 1 MCP

17

mcp-server-webcrawl

Advanced search and retrieval for web crawler data via MCP.

mcp-server-webcrawl provides an AI-oriented server that enables advanced filtering, analysis, and search over data from various web crawlers. Designed for seamless integration with large language models, it supports boolean search, filtering by resource types and HTTP status, and is compatible with popular crawling formats. It facilitates AI clients, such as Claude Desktop, with prompt routines and customizable workflows, making it easy to manage, query, and analyze archived web content. The tool supports integration with multiple crawler outputs and offers templates for automated routines.

32 7 MCP

18

Agentic Long-Term Memory with Notion Integration

Production-ready agentic long-term memory and Notion integration with Model Context Protocol support.

Agentic Long-Term Memory with Notion Integration enables AI agents to incorporate advanced long-term memory capabilities using both vector and graph databases. It offers comprehensive Notion workspace integration along with a production-ready Model Context Protocol (MCP) server supporting HTTP and stdio transports. The tool facilitates context management, tool discovery, and advanced function chaining for complex agentic workflows.

4 2 MCP

19

TrackMage MCP Server

Shipment and logistics tracking MCP server with multi-carrier support.

TrackMage MCP Server implements the Model Context Protocol (MCP) to provide shipment tracking, logistics management, and API integration for over 1,600 carriers worldwide. It allows integration with major LLMs, supports resources such as workspaces, shipments, orders, carriers, and tracking statuses, and offers tools to create, update, and monitor shipments and orders. The server supports OAuth-based authentication, flexible configuration via environment variables, and can be deployed locally for customized logistics operations.

1 4 MCP

20

Memory MCP

A Model Context Protocol server for managing LLM conversation memories with intelligent context window caching.

Memory MCP provides a Model Context Protocol (MCP) server for logging, retrieving, and managing memories from large language model (LLM) conversations. It offers features such as context window caching, relevance scoring, and tag-based context retrieval, leveraging MongoDB for persistent storage. The system is designed to efficiently archive, score, and summarize conversational context, supporting external orchestration and advanced memory management tools. This enables seamless handling of conversation history and dynamic context for enhanced LLM applications.

10 6 MCP

21

Raygun MCP Server

Access and interact with Raygun crash reporting data via Model Context Protocol for AI assistants.

Raygun MCP Server provides a remote MCP endpoint that enables AI assistants to securely access, analyze, and manage crash reporting and real user monitoring data from Raygun through natural language conversations. It supports various AI tools and assistants, allowing users to investigate errors, monitor deployments, track user sessions, and gather performance insights seamlessly. Integration is streamlined with step-by-step guides for connecting through multiple popular AI environments.

19 13 MCP

22

MCP Server for Deep Research

Transform research questions into comprehensive, well-cited reports using an advanced research assistant.

MCP Server for Deep Research provides an end-to-end workflow for conducting in-depth research on complex topics. It elaborates on research questions, generates subquestions, integrates web search, analyzes and synthesizes retrieved content, and generates structured, well-cited research reports. The tool integrates with Claude Desktop and leverages prompt templates tailored for comprehensive research tasks.

187 23 MCP

23

DuckDuckGo Search MCP Server

A Model Context Protocol server for DuckDuckGo web search and intelligent content retrieval.

DuckDuckGo Search MCP Server provides web search capabilities through DuckDuckGo, with advanced content fetching and parsing tailored for large language models. It supports rate limiting, error handling, and delivers results in an LLM-friendly format. The server is designed for seamless integration with AI applications and tools like Claude Desktop, enabling enhanced web search and content extraction through the Model Context Protocol.

637 118 MCP

24

GIS MCP Server

Empower AI with advanced geospatial operations via Model Context Protocol.

GIS MCP Server provides a Model Context Protocol (MCP) server implementation that enables Large Language Models to access and perform sophisticated GIS operations. It bridges AI assistants with Python geospatial libraries such as Shapely, GeoPandas, PyProj, Rasterio, and PySAL. The server supports a wide range of spatial analysis, coordinate transformations, raster and vector data processing, and geospatial intelligence tasks. By integrating with MCP-compatible clients, it enhances AI tools with precise and extensible spatial capabilities.

70 21 MCP

25

Octagon Deep Research MCP

AI-powered, enterprise-grade deep research server for MCP clients.

Octagon Deep Research MCP provides specialized AI-driven research and analysis via seamless integration with MCP-enabled applications. It offers comprehensive multi-source data aggregation, advanced analysis tools, and generates in-depth reports across various domains. The solution emphasizes high performance with no rate limits, enterprise-grade speed, and universal compatibility for teams needing thorough research capabilities.

70 12 MCP

26

Lucidity MCP

Intelligent prompt-based code quality analysis for AI coding assistants.

Lucidity MCP is a Model Context Protocol (MCP) server that empowers AI coding assistants to deliver high-quality code through intelligent, prompt-driven analysis. It offers comprehensive detection of code issues across multiple quality dimensions, providing structured and actionable feedback. With language-agnostic capabilities, extensible framework, and flexible transport options, Lucidity MCP seamlessly integrates into developer workflows and AI systems.

72 20 MCP

27

Mem0 MCP Server

Structured management of coding preferences using Mem0 and Model Context Protocol.

Mem0 MCP Server implements a Model Context Protocol-compliant server for storing, retrieving, and searching coding preferences. It integrates with Mem0 and offers tools for persistent management of code snippets, best practices, and technical documentation. The server exposes an SSE endpoint for clients like Cursor, enabling seamless access and interaction with coding context data.

506 104 MCP

28

Jotdown

MCP Server for Notion Page Creation and mdBook Generation

Jotdown is an MCP server enabling large language models to interact seamlessly with Notion and generate markdown books (mdBooks). It allows LLMs to create or update Notion pages and manage the entire process of markdown book creation, including structure and navigation. Leveraging the Model Context Protocol, it provides tools for consistent and intelligent context handling between LLMs and external content platforms.

19 4 MCP

29

MCP Server for the RAG Web Browser Actor

Local MCP server enabling LLMs to browse and extract web content via RAG Web Browser integration.

Implements a Model Context Protocol (MCP) server designed for integration with LLMs and Retrieval-Augmented Generation (RAG) pipelines, providing automated web search and web page extraction capabilities. Runs locally and interacts with the RAG Web Browser Actor in Standby mode, responding to queries by fetching, scraping, and returning cleaned content from the web as Markdown. Supports Google Search queries and direct URL fetching through a standardized 'search' tool interface, offering multiple output formats and programmable arguments. Deprecated in favor of mcp.apify.com but illustrates MCP server use for local web browsing integrations.

194 25 MCP

30

ImageSorcery MCP

Local image recognition and editing tools for AI assistants

ImageSorcery MCP provides AI assistants with advanced image processing capabilities, all executed locally for privacy and efficiency. It offers a suite of tools for editing, analyzing, and enhancing images, including cropping, resizing, object detection, and OCR. The software leverages pre-trained models and OpenCV techniques to handle a wide range of image tasks without requiring cloud services. Designed for AI integration, it allows natural language prompts to control image manipulation and recognition workflows.

236 30 MCP

31

OSP Marketing Tools for LLMs

Comprehensive marketing content creation and optimization tools for LLMs using MCP.

OSP Marketing Tools for LLMs offers a suite of marketing content creation and optimization utilities designed to operate with Large Language Models that support the Model Context Protocol (MCP). Built on Open Strategy Partners’ proprietary methodologies, it provides structured workflows for product value mapping, metadata generation, content editing, technical writing, and SEO guidance. The suite includes features for persona development, value case documentation, semantic editing, and technical writing best practices, enabling consistent and high-quality marketing outputs. Designed to integrate seamlessly with MCP-compatible LLM clients, it streamlines complex marketing processes and empowers efficient collaboration across technical and non-technical teams.

252 40 MCP

32

melrose-mcp

An MCP server for generating and playing programmable music via Melrōse.

melrose-mcp is a Model Context Protocol (MCP) server that enables users to compose and perform music using the Melrōse programming language. It facilitates communication between AI models and the Melrōse tool, allowing for dynamic manipulation of tempo, playback, and MIDI configuration. The project supports various tools for controlling musical expression and can be integrated into client applications such as Claude Desktop.

7 3 MCP

33

Rust Docs MCP Server

Serving up-to-date Rust crate documentation as an MCP server for coding assistants.

Rust Docs MCP Server provides AI coding assistants with a focused tool to query current documentation for specific Rust crates. It runs as a standard MCP server over stdio, enabling context-driven semantic searches and LLM-generated answers based only on retrieved documentation. It fetches crate docs, generates embeddings, and leverages OpenAI APIs for accurate and relevant code support, with support for caching and multi-crate operation.

208 30 MCP

34

mcp-server-qdrant

Official Model Context Protocol server for seamless integration with Qdrant vector search engine.

mcp-server-qdrant provides an official implementation of the Model Context Protocol for interfacing with the Qdrant vector search engine. It enables storing and retrieving contextual information, acting as a semantic memory layer for LLM-driven applications. Designed for easy integration, it supports environment-based configuration and extensibility via FastMCP. The server standardizes tool interfaces for managing and querying contextual data using Qdrant.

1,054 187 MCP

35

Agentset MCP

Open-source MCP server for Retrieval-Augmented Generation (RAG) document applications.

Agentset MCP provides a Model Context Protocol (MCP) server designed to power context-aware, document-based applications using Retrieval-Augmented Generation. It enables developers to rapidly integrate intelligent context retrieval into their workflows and supports integration with AI platforms such as Claude. The server is easily installable via major JavaScript package managers and supports environment configuration for namespaces, tenant IDs, and tool descriptions.

22 10 MCP

36

RivalSearchMCP

Advanced MCP server for web research, discovery, and trend analysis.

RivalSearchMCP is an advanced Model Context Protocol (MCP) server designed to streamline web research, content discovery, and trend analysis. It offers tools for multi-engine web search, intelligent content retrieval, website analysis, and AI-driven content insights. The platform includes integrated trends analysis, research workflows with progress tracking, and automated generation of LLMs.txt documentation files. Its anti-detection features, real-time content streaming, and flexible data export options make it ideal for complex research and automation workflows.

10 7 MCP

37

ApeRAG

Hybrid RAG platform with MCP integration for intelligent knowledge management

ApeRAG is a production-ready Retrieval-Augmented Generation (RAG) platform that integrates graph-based, vector, and full-text search capabilities. It enables the construction of knowledge graphs and supports MCP (Model Context Protocol), allowing AI assistants direct interaction with knowledge bases. Features include advanced document parsing, multimodal processing, intelligent agent workflows, and enterprise management tools. Deployment is streamlined via Docker and Kubernetes, with extensive support for customization and scalability.

920 96 MCP

38

Sourcerer MCP

Semantic code search & navigation MCP server for efficient AI agent context retrieval.

Sourcerer MCP provides a Model Context Protocol (MCP) server that enables AI agents to perform semantic code search and navigation. By indexing codebases at the function, class, and chunk level, it allows agents to retrieve only the necessary code snippets, greatly reducing token consumption. The tool integrates with Tree-sitter for language parsing and OpenAI for generating code embeddings, supporting advanced contextual code understanding without full file ingestion.

95 11 MCP

39

Vercel AI SDK Documentation MCP Agent

AI-powered documentation agent for Vercel AI SDK with Model Context Protocol support.

The Vercel AI SDK Documentation MCP Agent is a server implementing the Model Context Protocol to enable AI-powered search and conversational querying of the Vercel AI SDK documentation. It features natural language understanding, semantic search using FAISS, and session-based context management for in-depth assistance. Integration with popular MCP clients like Claude Desktop and Cursor ensures seamless use in developer workflows. Automated documentation indexing and a Gemini-powered agent enhance accuracy and contextuality of responses.

41 8 MCP

40

Graphlit MCP Server

Integrate and unify knowledge sources for RAG-ready AI context with the Graphlit MCP Server.

Graphlit MCP Server provides a Model Context Protocol interface, enabling seamless integration between MCP clients and the Graphlit platform. It supports ingestion from a wide array of sources such as Slack, Discord, Google Drive, email, Jira, and GitHub, turning them into a searchable, RAG-ready knowledge base. Built-in tools allow for document, media extraction, web crawling, and web search, as well as advanced retrieval and publishing functionalities. The server facilitates easy configuration, sophisticated data operations, and automated notifications for diverse workflows.

369 49 MCP

41

CrateDocs MCP

MCP server for Rust crate documentation lookup and search

CrateDocs MCP is an MCP (Model Context Protocol) server designed to provide AI models with access to Rust crate documentation. It enables lookup of crate-level and item-level documentation, as well as efficient searching of Rust crates on crates.io. The system supports various server modes, offers multiple output formats, and includes features for both developers and large language models.

9 2 MCP

42

MCP-Typescribe

An MCP server for serving TypeScript API context to language models.

MCP-Typescribe is an open-source implementation of the Model Context Protocol (MCP) focused on providing LLMs with contextual, real-time access to TypeScript API documentation. It parses TypeScript (and other) definitions using TypeDoc-generated JSON and serves this information via a queryable server that supports tools used by AI coding assistants. The solution enables AI agents to dynamically explore, search, and understand unknown APIs, accelerating onboarding and supporting agentic behaviors in code generation.

45 6 MCP

43

GitMCP

Instantly turn any GitHub repository into an AI-ready documentation hub.

GitMCP is a free, open-source, remote Model Context Protocol (MCP) server that gives AI assistants real-time access to the latest documentation and code from any GitHub repository. It transforms any GitHub project into an accessible documentation hub, enabling AI tools to deliver accurate results, reduce hallucinations, and improve code correctness. Supporting both specific and generic server modes, it allows seamless integration into developer workflows with zero setup. GitMCP emphasizes privacy, flexibility, and up-to-date information retrieval.

6,916 571 MCP

44

Chroma MCP Server

A self-hosted Model Context Protocol (MCP) server for Chroma vector database integration.

Chroma MCP Server implements the Model Context Protocol to allow seamless integration between LLM applications and external data using the Chroma embedding database. It enables AI models to create, manage, and query collections with advanced vector search, full text search, and metadata filtering. The server supports both ephemeral and persistent client types, along with integration for HTTP and cloud-based Chroma instances. Multiple embedding functions, collection management tools, and rich document operations are available for extensible LLM workflows.

418 78 MCP

45

MCP Language Server

Bridge codebase navigation tools to AI models using MCP-enabled language servers.

MCP Language Server implements the Model Context Protocol, allowing MCP-enabled clients, such as LLMs, to interact with language servers for codebase navigation. It exposes standard language server features—like go to definition, references, rename, and diagnostics—over MCP for seamless integration with AI tooling. The server supports multiple languages by serving as a proxy to underlying language servers, including gopls, rust-analyzer, and pyright.

1,256 94 MCP

46

awslabs/mcp

Specialized MCP servers for seamless AWS integration in AI and development environments.

AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.

6,220 829 MCP

47

CRIC物业AI MCP Server

行业级物业AI智能体，基于MCP协议的多场景助手

CRIC物业AI MCP Server is a server-side implementation based on the Model Context Protocol (MCP), offering intelligent assistance specifically for the property management sector. It integrates multi-modal large models and RAG technology to provide industry research, legal insights, community governance, project operations, and copywriting support. The platform leverages extensive proprietary datasets and real-time data monitoring to deliver accurate, context-driven services for diverse property-related business scenarios.

1 3 MCP

48

mcp-server-atlassian-confluence

Seamlessly connect AI assistants to your Atlassian Confluence knowledge base.

Enables integration of AI assistants like Claude and Cursor AI directly with Atlassian Confluence, allowing users to interact with their documentation and knowledge base using natural language queries. Supports instant answers, search across all spaces, and access to specific Confluence content and discussions. Follows the Model Context Protocol (MCP) for standardized model context management and easy configuration with various AI assistants via STDIO transport or config files.

39 20 MCP

49

VikingDB MCP Server

MCP server for managing and searching VikingDB vector databases.

VikingDB MCP Server is an implementation of the Model Context Protocol (MCP) that acts as a bridge between VikingDB, a high-performance vector database by ByteDance, and AI model context management frameworks. It allows users to store, upsert, and search vectorized information efficiently using standardized MCP commands. The server supports various operations on VikingDB collections and indexes, making it suitable for integrating advanced vector search in AI workflows.

3 5 MCP

50

Multi-Database MCP Server (by Legion AI)

Unified multi-database access and AI interaction server with MCP integration.

Multi-Database MCP Server enables seamless access and querying of diverse databases via a unified API, with native support for the Model Context Protocol (MCP). It supports popular databases such as PostgreSQL, MySQL, SQL Server, and more, and is built for integration with AI assistants and agents. Leveraging the MCP Python SDK, it exposes databases as resources, tools, and prompts for intelligent, context-aware interactions, while delivering zero-configuration schema discovery and secure credential management.

76 19 MCP

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