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"Using an AI Agent for Structured Search and Traversal in a Neo4j Database" matching MCP servers:

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    MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.
    15
    MIT
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    B
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    MCP server for noise-reduced X (Twitter) search planning and Feedback-to-Fix engineering handoffs. Enables AI agents to generate structured search plans, filter signals, and build handoff packages via MCP tools.
    1
    MIT
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    A
    quality
    D
    maintenance
    MCP server for AI agents providing 300 curated Japanese home & lifestyle products across 31 categories. Features mm-precision dimension search, related-item chains (1 product → 3-5 accessories), shelf+storage coordination, and Rakuten/Amazon affiliate links.
    15
    25
    1
    MIT
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    B
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    MCP server for managing Tokei pre-launch and waitlist campaigns, wrapping the Tokei v1 REST API. Enables querying pages, stats, leaderboards, signups, and performing write operations like cloning pages and uploading media through natural language.
    313
    MIT
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    Headless MCP server for Simpson Strong-Tie product data. Provides AI agents with structural connector lookups, load calculations, code compliance verification, and engineering specifications.
    MIT
  • F
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    quality
    C
    maintenance
    Gives Claude four decision tools for product management: rank backlog, mine customer feedback, size sprint capacity, and trace dependency risk, all grounded in JSON data.
  • F
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    B
    maintenance
    MCP server providing tools for product management decision-making including backlog prioritization, feedback analysis, capacity assessment, and dependency mapping.
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    B
    maintenance
    Remote MCP server for Pruva, enabling AI assistants to manage products, features, and documents over HTTPS with OAuth authentication.
    MIT
  • A
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    quality
    C
    maintenance
    Connects AI agents to the Outset research platform for creating studies, managing recruitment, and querying results via the Model Context Protocol.
    MIT
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    D
    maintenance
    Enables AI assistants to search Sunex's lens and imager catalog using natural language queries. It provides tools for finding compatible lenses, sensor specifications, and product details through a public Model Context Protocol server.
    MIT
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    quality
    C
    maintenance
    Enables AI agents to interact with VoteShip feature requests, voting boards, roadmaps, and changelogs, including public board access without credentials and authenticated project administration with a project secret.
    MIT
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    quality
    A
    maintenance
    Generates structured, validated PRDs from feature descriptions via a staged reducer pipeline. Provides MCP tools for pipeline control, section/document validation, context budgeting, and failure-to-retrieval mapping.
    2
    MIT