"Information about MCP Proxy" matching MCP servers:

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

A Model Context Protocol server that allows AI agents to perform WHOIS lookups, enabling users to directly ask the AI about domain availability, ownership, registration details, and other domain information.

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.

Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.

Plugged.in MCP Server acts as a proxy server that combines multiple MCP servers into a single interface. It retrieves tool, prompt, and resource configurations from Plugged.in and directs requests for tools, prompts, and resources to the appropriate underlying server.

A Model Context Protocol server that provides natural language access to Cortex API, enabling users to query information about their system's structure and make faster decisions about services, incidents, and team responsibilities.

MCP Memory is an MCP Server that gives MCP Clients the ability to remember information about users across conversations. It uses vector search technology to find relevant memories based on meaning, not just keywords.

Enables LLMs to perform sophisticated web searches through proxy servers using Tavily's API, supporting comprehensive web searches, direct question answering, and recent news article retrieval with AI-extracted content.

A config-driven MCP server that exposes OData and REST APIs as MCP tools, enabling AI assistants to query, manage, and monitor SAP backends through natural language.

A comprehensive MCP proxy server that bridges MCP clients with Ollama local language models, providing advanced features like RAG integration, context management, caching, and production-ready security.

Enables users to query information about LPDP scholarship financial disbursement using RAG with Pinecone vector search and Gemini 2.0 Flash, answering questions about funding components, deadlines, living allowances, and required documents.

Enables clients of tool-heavy MCP aggregators to find and use upstream tools on demand through four fixed bridge tools (search, describe, call, refresh), cutting per-turn tool context from ~180k tokens to ~2–3k. It merges multiple upstream servers behind sticky sessions and a local lexical BM25 index, so only the schemas actually needed are retrieved.

A flexible proxy that enables discovery and execution of tools across multiple Model Context Protocol (MCP) servers and JavaScript functions, reducing context size even when dealing with hundreds of tools.

Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.

A semantic proxy that reduces AI agent token usage by exposing only three core tools and using local vector embeddings to search for and execute hundreds of underlying MCP tools. It streamlines communication between agents and MCP Routers by identifying relevant tools through natural language queries.

Bridges STDIO-based MCP clients with SSE-based MCP servers, allowing applications like Claude Desktop to connect to remote MCP servers that use SSE transport.

An MCP server that provides country-related data from the REST Countries API, allowing users to query information about countries through natural language.

Reverse proxy for the Tavily MCP endpoint that bypasses geo-blocking, rotates API keys based on quota, and authenticates clients via access keys.

A Compact Knowledge Graph MCP server providing pre-structured domain knowledge as a routing layer for agent stacks, enabling efficient structural queries (e.g., prerequisites, dependency chains) without hallucinations.

Enables searching and reading AVEVA Customer Support Portal knowledge base articles, including tech notes, known issues, and error-message diagnostics, to ground AI answers in support content not found in public documentation.