"A server for orchestrating and validating AI agents" matching MCP servers:

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

A Model Context Protocol server that enables Claude users to access specialized OpenAI agents (web search, file search, computer actions) and a multi-agent orchestrator through the MCP protocol.

An MCP server that runs AI-driven venture capitalist agents whose thinking is continuously enriched by Octagon Private Markets' real-time deals and intelligence for pitch feedback, diligence simulations, and term sheet negotiations.

A 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.

A multi-agent product-management copilot that automates morning briefings, metrics answers, knowledge lookups over an Obsidian vault, and PRD/ticket drafting.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

Interact with WebScraping.AI API for web data extraction and scraping

A proof of concept MCP server for Apache OFBiz

Give long term memory to your agents without building the RAG pipelines.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables Claude Desktop to search private documents using Azure AI Search and perform web searches with Bing, providing AI-enhanced results with source citations through Azure AI Agent Service or direct Azure AI Search integration.

Integrates Claude Desktop with Azure AI Search, allowing users to query search indexes using keyword, vector, or hybrid search methods.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.

Extends large language model context length up to 60 times using gravitational memory, designed for Claude Code and Anthropic AI models.

Extends LLM context windows by 15-60× using gravitational memory compression, enabling massive context extension for codebases, research papers, and long documents.