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    A Model Context Protocol (MCP) server that implements an advisor-based consensus mechanism for collaborative problem-solving using multiple AI models, enabling structured discussion and debate among 5 specialized advisors to reach optimal solutions.
    1
    16 npm
    1
    MIT
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    A Model Context Protocol server that provides access to Aiven services (PostgreSQL, Kafka, ClickHouse, Valkey, OpenSearch), enabling LLMs to build full stack solutions by interacting with these services.
    3
    245 npm
    28
    Apache 2.0
  • A
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    Connects MCP clients to the 638Labs registry to discover, route, and auction tasks across diverse AI agents. It enables price-based auctions where agents compete to provide the most cost-effective solutions for tasks like coding, translation, and data extraction.
    18 npm
    1
    MIT
  • A
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    This read-only MCP Server allows you to connect to SurveyMonkey data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp
    2
    MIT
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    webnav is an MCP server that gives web-browsing AI agents a reusable, deterministic site map, so they stop re-exploring sites every run. It enables page-to-page navigation with zero LLM overhead, pausing only at genuine decision points.
    37 npm
    Apache 2.0
  • A
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    MCP server that connects AI agents to OpenHive — a shared knowledge base of problem-solution pairs contributed by AI coding agents. Search thousands of real solutions, post new discoveries, and upvote what works. Works with Claude Desktop, Kiro, Cursor, Windsurf, Cline, and any MCP-compatible client.
    3
    72 npm
    5
    MIT
  • A
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    Enables connecting over 1,000 apps once, self-hosted and with encrypted credentials, so that Claude, Codex, Cursor, Copilot and dozens of other AI agents can call their APIs as MCP tools. Agents authenticate with per-agent tokens to get ready-made tools for every connected app, including app-specific actions like searching mail or sending messages.
    1
    1,084 npm
    4
    MIT
  • F
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    Enables autonomous learning from interactions through pattern recognition and machine learning techniques. Continuously improves performance by analyzing tool usage, providing predictive suggestions, and sharing knowledge across MCP servers.
    8
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  • A
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    Aggregates tools from multiple upstream MCP servers and exposes them through 4 meta-tools, enabling LLMs to discover and use hundreds of tools without loading all schemas upfront.
    430 PyPI
    3
    Apache 2.0
  • A
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    A2A Grocery is the Agent-to-Agent (A2A) + Model Context Protocol (MCP) hub for retail grocery procurement. It puts makers, brand owners, private label, distributors and importers in front of the AI agents that now do the grocery buying, and gives retail procurement desks every cleared supplier's record, ready to order. 20 markets on the SCHEMA algo record. No ads. No rank for sale. Trade only.
    MIT