"Managing Multiple MCP Servers" matching MCP servers:

A TypeScript MCP server that provides secure, read-only access to a locally hosted MySQL database for AI-agent workflows, with configurable policies and support for multiple MCP clients.

Generates, validates, and updates structured research tables by synthesizing multiple AI queries, enabling AI agents to autonomously drive research workflows.

An intelligent MCP server that orchestrates multiple MCP servers with AI-enhanced workflow automation and production-ready context engine capabilities for codebase analysis.

A Model Context Protocol server for managing prompt templates as markdown files with YAML frontmatter, allowing users and LLMs to easily add, retrieve, and manage prompts.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.

Enables AI agents to interact with the AI-Archive platform for research paper discovery through semantic search, paper submission and management, peer review with structured scoring, and citation generation in multiple formats.

Provides semantic search and data retrieval capabilities over a knowledge base with multiple tools including keyword search, category filtering, and ID-based lookup with in-memory caching.

A Model Context Protocol server enabling AI assistants to scrape web content with high accuracy and flexibility, supporting multiple scraping modes and content formatting options.

An MCP server for querying and managing LlamaIndex documents stored in Qdrant vector databases, with automatic embedding model detection and extensive tools for search, retrieval, and collection management.

An MCP server integrating Perplexity AI's API to offer advanced search capabilities with support for multiple models and result configuration.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

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Combines a knowledge graph with RAG (Retrieval-Augmented Generation) capabilities for semantic code indexing and search. Enables creating entity relationships, managing observations, and performing semantic searches across indexed codebases.

A server that enables communication with multiple unichat-based MCP servers simultaneously, allowing users to query different language models and combine their responses for more comprehensive results.

A TypeScript-based template for developing Model Context Protocol servers with features like dependency injection and service-based architecture, facilitating the creation and integration of custom data processing tools.

MCP server for Teradata databases, providing tools and prompts for querying, analyzing, and managing data through AI agents.

An MCP server that routes LLM requests across multiple providers and orchestrates other MCP servers, with a focus on local privacy for embeddings and memory.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

A comprehensive Model Context Protocol server that enables interaction with the Klaviyo API, providing tools and resources for managing customer profiles, lists, segments, campaigns, flows, and various marketing automation features.

Model Context Protocol (MCP) is a new, standardized protocol for managing context between large language models (LLMs) and external systems. In this repository, we provide an installer as well as an MCP Server for Upstash Developer API's.