Trieve - Alternatives & Competitors
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.
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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 -
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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 -
3
Pearch.ai MCP
Natural Language People Search and Candidate Sourcing API for Seamless ATS Integration
Pearch.ai MCP provides a high-precision people search API that interprets natural language queries to deliver top-quality candidate results. Designed for easy integration with Applicant Tracking Systems and hiring platforms, it leverages scientific methods and is trusted by recruiters. The tool is implemented as a Model Context Protocol (MCP), facilitating standardized model context handling and deployment via packages like FastMCP or through Smithery. The solution prioritizes ease of use, reliability, and high candidate match accuracy.
5 4 MCP -
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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 -
5
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 -
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MCP-searxng
MCP server bridging agentic systems with SearXNG web search
MCP-searxng enables agentic systems to interface with web search engines via the SearXNG platform by implementing the Model Context Protocol. It supports both command-line and local server deployment, providing flexible integration options. Users can configure custom SearXNG server URLs and connect through clients like uvx or claude desktop. The tool simplifies access to structured web search within agentic workflows.
107 19 MCP -
7
NCBI Literature Search MCP Server
Seamless PubMed literature search via Model Context Protocol server.
NCBI Literature Search MCP Server provides a Model Context Protocol (MCP) interface to search the vast PubMed database using natural language queries. It enables AI assistants to conduct comprehensive and advanced literature searches across biological and biomedical disciplines, returning metadata such as abstracts, author lists, MeSH terms, and DOIs. Designed for integration with AI tools, it supports advanced query capabilities and streamlines literature review and research discovery processes.
6 1 MCP -
8
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 -
9
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 -
10
Naver Search MCP Server
Unified Naver Search and DataLab API integration for context-aware tools.
Naver Search MCP Server provides a Model Context Protocol (MCP) compliant server that integrates Naver Search and DataLab APIs. It enables easy and comprehensive search across a wide range of Naver services, as well as advanced trend analysis with context-aware tools. The implementation supports Smithery platform installation, temporal context handling, and offers tools for both information retrieval and data analytics within the Naver ecosystem.
45 20 MCP -
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Exa MCP Server
Fast, efficient web and code context for AI coding assistants.
Exa MCP Server provides a Model Context Protocol (MCP) server interface that connects AI assistants to Exa AI’s powerful search capabilities, including code, documentation, and web search. It enables coding agents to retrieve precise, token-efficient context from billions of sources such as GitHub, StackOverflow, and documentation sites, reducing hallucinations in coding agents. The platform supports integration with popular tools like Cursor, Claude, and VS Code through standardized MCP configuration, offering configurable access to various research and code-related tools via HTTP.
3,224 244 MCP -
12
Brave Search MCP Server
MCP integration for web, image, news, video, and local search via Brave Search API.
Implements a Model Context Protocol server that connects with the Brave Search API, enabling AI systems to perform comprehensive web, image, news, video, and local points of interest searches. Provides standardized MCP tools for various search types, each supporting advanced filtering parameters. Designed for easy integration in context-aware model interfaces such as Claude Code.
86 17 MCP -
13
SearXNG MCP Server
MCP-compliant server integrating the SearXNG API for advanced web search capabilities
SearXNG MCP Server implements the Model Context Protocol and integrates the SearXNG API to provide extensive web search functionalities. It features intelligent caching, advanced content extraction, and multiple configurable search parameters such as language, time range, and safe search levels. The server exposes tools for both web searching and URL content reading, supporting detailed output customization through input parameters. Designed for seamless MCP deployments, it supports Docker and NPX-based installation with rich configuration options.
321 56 MCP -
14
mcp-paperswithcode
Discover and analyze research papers and code repositories through the PapersWithCode API.
mcp-paperswithcode provides a Model Context Protocol (MCP) interface for AI assistants to discover, search, and analyze research papers, related code repositories, datasets, authors, conferences, and research areas. The tool enables seamless integration with the PapersWithCode API, offering powerful methods for context-aware research exploration. It supports searching, retrieving metadata, extracting content, and listing relationships between academic resources, enhancing an AI model's ability to access and utilize scientific content.
14 7 MCP -
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Kagi MCP Server
Integrate Kagi Search and Summarization as Model Context Protocol tools.
Kagi MCP Server enables easy integration of Kagi's search and summarization capabilities with AI systems via the Model Context Protocol. It facilitates tool-based queries such as searching web results or summarizing content, and offers setup instructions for various platforms including Claude Desktop. Users can install and configure the server through package managers, Smithery, or direct Python environments. The project provides configurable environment variables for API access and summarization engine selection, supporting both local development and production usage.
216 24 MCP -
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tavily-search MCP server
A search server that integrates Tavily API with Model Context Protocol tools.
tavily-search MCP server provides an MCP-compliant server to perform search queries using the Tavily API. It returns search results in text format, including AI responses, URLs, and result titles. The server is designed for easy integration with clients like Claude Desktop or Cursor and supports both local and Docker-based deployment. It facilitates AI workflows by offering search functionality as part of a standardized protocol interface.
44 11 MCP -
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Web Analyzer MCP
Intelligent web content analysis and summarization via MCP.
Web Analyzer MCP is an MCP-compliant server designed for intelligent web content analysis and summarization. It leverages FastMCP to perform advanced web scraping, content extraction, and AI-powered question-answering using OpenAI models. The tool integrates with various developer IDEs, offering structured markdown output, essential content extraction, and smart Q&A functionality. Its features streamline content analysis workflows and support flexible model selection.
2 3 MCP -
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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 -
19
OpenTK Model Context Protocol Server
A standardized interface for LLMs to access Dutch parliamentary data.
OpenTK Model Context Protocol Server provides a bridge between large language models and Dutch parliamentary data using the Model Context Protocol (MCP). It enables AI systems to access, search, and analyze parliamentary documents, debates, and member information from the Tweede Kamer through a unified and structured interface. By leveraging the @modelcontextprotocol/sdk, it ensures consistent context management for model interactions. Built atop the OpenTK project, it delivers streamlined access to extensive open government datasets.
16 3 MCP -
20
RAG Documentation MCP Server
Vector-based documentation search and context augmentation for AI assistants
RAG Documentation MCP Server provides vector-based search and retrieval tools for documentation, enabling large language models to reference relevant context in their responses. It supports managing multiple documentation sources, semantic search, and real-time context delivery. Documentation can be indexed, searched, and managed with queueing and processing features, making it highly suitable for AI-driven assistants. Integration with Claude Desktop and support for Qdrant vector databases is also available.
238 29 MCP -
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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 -
22
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 -
23
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 -
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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 -
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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 -
26
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 -
27
Serena
Coding agent toolkit with IDE-like semantic code retrieval and editing for LLM integration.
Serena is a free and open-source coding agent toolkit that enhances large language models with advanced semantic code retrieval and editing tools. It enables integration through the Model Context Protocol (MCP), allowing seamless operation with various coding agents, IDEs, and interfaces. Serena extracts code entities at the symbol level, supports context-aware operations, and improves token efficiency for coding tasks. The tools can be incorporated into diverse LLM-driven environments for more efficient and precise code editing.
15,643 1,038 MCP -
28
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 -
29
Wren Engine
Semantic Engine for MCP Clients and AI Agents
Wren Engine is a semantic engine designed for Model Context Protocol (MCP) clients and AI agents. It enables precise access to enterprise data by providing semantic understanding, trusted aggregations, and business term clarity across numerous data sources. With a focus on accurate context, calculation, and governance, it equips AI systems to interact safely and meaningfully with complex enterprise data. As part of the MCP ecosystem, it connects LLMs with databases and enterprise tools through standardized protocols.
496 138 MCP -
30
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 -
31
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 -
32
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 -
33
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 -
34
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 -
35
Octocode MCP
Enterprise-grade AI context server for codebase research and analysis.
Octocode MCP is a Model Context Protocol (MCP) server designed to enable AI assistants to search, analyze, and extract insights from millions of GitHub repositories with high security and token efficiency. It offers intelligent orchestration for deep code research, planning, and agentic workflows, streamlining the process of building and understanding complex software projects. The platform features robust tools and commands, such as /research for expert code research, designed to support developers and AI systems with context-rich information.
577 45 MCP -
36
mcp-pinecone
A Pinecone-backed Model Context Protocol server for semantic search and document management.
mcp-pinecone implements a Model Context Protocol (MCP) server that integrates with Pinecone indexes for use with clients such as Claude Desktop. It provides powerful tools for semantic search, document reading, listing, and processing within a Pinecone vector database. The server supports operations like embedding, chunking, and upserting records, enabling contextual management of large document sets. Designed for ease of installation and interoperability via the MCP standard.
150 35 MCP -
37
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 -
38
FHIR MCP Server
A Model Context Protocol server for seamless interaction with FHIR resources and AI tools.
FHIR MCP Server implements a full Model Context Protocol server, enabling large language model agents to perform comprehensive CRUD operations on FHIR-compliant healthcare data. It offers standardized integration with various clinical data sources, natural-language query capabilities, and supports secure authentication via OAuth2. The server includes semantic search, AI-powered document processing, terminology resolution, Docker deployment, and is optimized for use with MCP-compatible clients like Claude Desktop.
34 5 MCP -
39
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 -
40
Smart Tree
Lightning Fast Directory Visualization and AI-Enabled Context Compression.
Smart Tree is a high-performance directory visualization tool built with Rust, offering advanced context management and AI-integrated features. It supports persistent memory anchoring, compressed context formats for reduced token usage, and real-time, interactive terminal UI via Spicy TUI mode. The tool provides programmatic hooks for MCP compliance, enabling AI assistants to recall and leverage project insights efficiently.
175 15 MCP -
41
Everything Search MCP Server
Fast, cross-platform file search via Model Context Protocol integration.
Everything Search MCP Server provides fast file and folder search capabilities across Windows, macOS, and Linux platforms as an MCP server. It leverages native search utilities such as the Everything SDK on Windows, mdfind on macOS, and locate/plocate on Linux. The tool exposes a standardized search interface with customizable parameters including query, sorting, and matching options. It is suitable for integration with AI clients or automation tools that follow the Model Context Protocol.
268 35 MCP -
42
anyquery
Universal SQL query engine for files, databases, apps, and LLM integration.
Anyquery is a SQL query engine that enables users to run SQL queries on a wide array of data sources, including files, databases, and popular applications via plugins. It supports integrations with large language models (LLMs) through the Model Context Protocol (MCP), providing seamless access for AI models to query data. Built on SQLite, it extends functionality with a plugin system and can also function as a MySQL server for compatibility with conventional SQL clients. Its flexible installation options and broad plugin ecosystem allow extensive customization and integration.
1,298 77 MCP -
43
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 -
44
Memcord
Privacy-first, self-hosted chat memory and context management for Claude and AI applications.
Memcord serves as a self-hosted MCP (Model Context Protocol) server that enables users to securely organize, summarize, and search through their chat history with AI, especially for Claude, without compromising privacy. It offers intelligent memory management, conversation auto-summarization, deduplication, and context merging to build a searchable knowledge base across multiple conversations. Memcord also integrates seamlessly with Claude Desktop, VSCode, and supports various installation methods for flexibility.
18 5 MCP -
45
CICADA
Structured, contextual code intelligence for AI assistants on Elixir projects.
CICADA is an MCP server that provides AI assistants with AST-level, structured access to Elixir codebases. It enables code analysis, semantic search, module and function discovery, and git/PR attribution for deeper contextual understanding. CICADA supports multiple editors and offers features like dependency mapping, dead-code detection, and local indexing with strong privacy guarantees.
11 2 MCP -
46
Weaviate MCP Server
A server implementation for the Model Context Protocol (MCP) built on Weaviate.
Weaviate MCP Server provides a backend implementation of the Model Context Protocol, enabling interaction with Weaviate for managing, inserting, and querying context objects. The server facilitates object insertion and hybrid search retrieval, supporting context-driven workflows required for LLM orchestration and memory management. It includes tools for building and running a client application, showcasing integration with Weaviate's vector database.
157 38 MCP -
47
Zettelkasten MCP Server
A Zettelkasten-based knowledge management system implementing the Model Context Protocol.
Zettelkasten MCP Server provides an implementation of the Zettelkasten note-taking methodology, enriched with bidirectional linking, semantic relationships, and categorization of notes. It enables creation, exploration, and synthesis of atomic knowledge using MCP for AI-assisted workflows. The system integrates with clients such as Claude and supports markdown, advanced search, and a structured prompt framework for large language models. The dual storage architecture and synchronous operation model ensure flexibility and reliability for managing personal or collaborative knowledge bases.
114 21 MCP -
48
OpenAI WebSearch MCP Server
Intelligent web search with OpenAI reasoning model support, fully MCP-compatible.
OpenAI WebSearch MCP Server provides advanced web search functionality integrated with OpenAI's latest reasoning models, such as gpt-5 and o3-series. It features full compatibility with the Model Context Protocol, enabling easy integration into AI assistants that require up-to-date information and contextual awareness. Built with flexible configuration options, smart reasoning effort controls, and support for location-based search customization. Suitable for environments such as Claude Desktop, Cursor, and automated research workflows.
75 18 MCP -
49
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 -
50
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
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