A
licenseB
qualityF
maintenanceAn MCP server that enables users to retrieve information from AWS Knowledge Bases using RAG (Retrieval-Augmented Generation) via Bedrock Agent Runtime.
Last updated
1
115
MIT
59,919 servers. Last updated
Search Relevance ↓
Recent Usage ↓
Date Added ↓
Date Updated ↓
Weekly Downloads ↓
GitHub Stars ↓
Recent GitHub Stars ↓
Matching MCP tools:
Matching MCP Connectors:
io.github.eins78
io.github.pipeworx-io
com.adspirer
io.github.CSOAI-ORG
"Ars Technica" matching MCP servers:
TorchV AIS MCP Serverofficial
AlicenseDqualityDmaintenanceEnables read, write, edit, and file transfer operations on TorchV AIS enterprise knowledge bases. Supports document management, repository browsing, and administrative tasks with configurable readonly, write, or admin permission levels.Last updated8153Apache 2.0- Alicense-qualityDmaintenanceEnables Claude to intelligently query and analyze your resume using RAG technology. Supports skill matching against job requirements and answering questions about your professional background from locally stored resume files.Last updatedMIT
- Alicense-qualityDmaintenanceA vector search system that enables semantic retrieval of document chunks using MongoDB Atlas Vector Search and Voyage AI embeddings, allowing users to search documents by meaning rather than just keywords.Last updated2MIT
- Alicense-qualityDmaintenanceCTX is a tool made to solve a big problem when chatting with LLMs like ChatGPT or Claude: giving them enough context about your project.Last updated329MIT
- Alicense-qualityBmaintenanceMCP server that provides tools to add to, search, and manage a wiki knowledge base, enabling AI chat tools to contribute and retrieve information from the wiki via natural language prompts.Last updatedMIT
- Alicense-qualityDmaintenanceAn MCP server that provides custom prompts for guiding bot interactions, specifically to avoid using brackets in descriptions.Last updated1MIT
- Alicense-qualityCmaintenancePersistent memory for AI agents — organized by time and space. Important memories get promoted, noise decays naturally, and related knowledge clusters into a browsable topic tree. Fully automatic.Last updated27MIT
- Alicense-qualityDmaintenanceThis 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 Snapchat Ads (beta): https://www.cdata.com/download/download.aspx?sku=JPZK-V&type=betaLast updated1MIT
- Alicense-qualityFmaintenanceA tool that connects Google Ads with Claude AI, allowing users to analyze advertising data through natural language conversations and access campaign information, performance metrics, keyword analytics, and ad management.Last updated663MIT
- Alicense-qualityDmaintenanceA lightweight framework for building and orchestrating AI agents through the Model Context Protocol, enabling users to create scalable multi-agent systems using only configuration files.Last updatedMIT
- Flicense-quality-maintenanceProvides AI agents with database-like operations over LanceDB with automatic BGE-M3 multilingual embedding generation, enabling semantic search, CRUD operations, and safe schema migrations across structured data.Last updated
- Flicense-qualityDmaintenanceA high-performance MCP server that connects tools like Cursor to Elasticsearch clusters using public-key authorization instead of API keys. It provides optimized tools for searching data, listing indices, and inspecting cluster mappings or shards with support for concurrent requests.Last updated
- -license-quality-maintenanceAn MCP server implementation that enables generation of Google Ads content through Claude Code, Claude Desktop, and other MCP-compatible clients.Last updated
- Flicense-qualityDmaintenanceExposes Dify applications (both Chatflow and Workflow) as MCP (Model Context Protocol) servers, allowing Claude and other MCP clients to directly interact with Dify apps through a standardized protocol.Last updated35
- Flicense-quality-maintenanceA minimal, well-structured MCP server implementation for learning and experimentation that exposes three tools: web search, API search, and client ID processing. It demonstrates clean separation between tool, transport, and LLM layers while supporting multiple AI clients through the Model Context Protocol standard.Last updated