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"A search for LinkedIn contacts who are decision makers in optical lab manufacturing in Europe" matching MCP servers:

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  • F
    license
    A
    quality
    D
    maintenance
    A versatile MCP server providing tools for arithmetic operations, n8n webhook integration, and access to a customer support playbook resource. It also includes specialized prompt templates for converting webinar transcripts into engaging blog posts.
    5
    2
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  • F
    license
    A
    quality
    F
    maintenance
    Enables LLMs to search and retrieve Autotask tickets, companies, and contacts using advanced semantic search and AI-powered reranking.
    11
    2
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  • A
    license
    Not graded
    quality
    C
    maintenance
    Laya-MLX as an MCP server (and plain-HTTP API). It answers typed decisions — choose an option / score a rubric / is this true? — on your own machine (Apple Silicon / MLX), with no cloud and ~10ms after warm-up. Not a chatbot. No token-by-token text, no JSON that can break. One forward pass returns a structured answer you can branch on. Ideal for routing, triage, classification, lead scoring, and g
    MIT
  • A
    license
    A
    quality
    F
    maintenance
    An MCP-compliant server that enables AI assistants like Claude Desktop to access and analyze Intercom support tickets with full conversation history.
    4
    8
    Apache 2.0
  • A
    license
    Not graded
    quality
    D
    maintenance
    Privacy-first Telegram MCP server enabling maintainers to triage chats, inspect context, search messages, draft replies, and send authorized messages locally without a cloud relay.
    42 npm
    1
    MIT
  • F
    license
    Not graded
    quality
    C
    maintenance
    Enables users to ask natural-language questions about why an account's bill changed and receive ranked, evidence-linked explanations grounded in computed SQL diffs, with enforced per-session authorization so agents cannot access unauthorized accounts or modify ledgers.
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  • F
    license
    Not graded
    quality
    D
    maintenance
    Enables interaction with Zendesk Support for managing tickets, comments, and filtering via the Model Context Protocol. It allows LLMs to perform actions like creating, updating, and listing support tickets through natural language in a Heroku-native environment.
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  • A
    license
    A
    quality
    B
    maintenance
    Enables Claude to search, create, and update contacts, deals, and support tickets in HubSpot, and to generate cross-object account summaries.
    10
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    MCP server for a production-shaped service-business agent, enabling grounded knowledge search, intake collection, and human escalation with deterministic safety boundaries.
    3
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    MCP server for Syncro MSP that enables managing customers, tickets, assets, contacts, and invoices through a decision tree architecture for efficient tool navigation.
    Apache 2.0
  • A
    license
    Not graded
    quality
    A
    maintenance
    MCP server for the Atera RMM API. Implements a decision tree architecture for efficient tool discovery, enabling Claude to manage devices, alerts, tickets, and customers in Atera.
    Apache 2.0
  • A
    license
    Not graded
    quality
    B
    maintenance
    An MCP server that lets AI agents search contacts, manage the call queue, log activities, and update deal stages in a CRM while preventing destructive actions and email sending.
    MIT
  • F
    license
    Not graded
    quality
    B
    maintenance
    Enables MCP clients to access and interact with a ServiceNow instance via its REST APIs, using per-user OAuth 2.0 token passthrough so ServiceNow ACLs are enforced for each signed-in user.
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  • F
    license
    Not graded
    quality
    C
    maintenance
    Exposes read-only knowledge base articles on returns, warranty and shipping policies alongside tools that search, retrieve and create real support tickets. This lets an LLM agent ground its answers in store policy without inventing information, and act on actual ticket data rather than simulated records.
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