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650,521 tools. Updated 2026-10-14 00:42

"Best servers to integrate with Claude AI" matching MCP tools:

  • Get Lenny Zeltser's CTI cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `cti_load_context`. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • INVERSE of simulate_mmc — given an arrival rate, service rate, and a target average wait time, returns the SMALLEST number of servers needed to meet the target. Use this when the user asks 'how many servers do I need?' / 'what staffing keeps wait under N minutes?'. The tool runs a binary search over candidate server counts (up to maxServers, default 50), invoking the simulator for each candidate. Saves Claude from iterating simulate_mmc 3-5 times by hand. If even maxServers servers can't meet the target, the recommendation is null and the response includes the achieved wait so Claude can explain that the target is infeasible at the given load. ANTI-FABRICATION: `recommendedServers` and `achievedAvgWaitMinutes` come from real DES runs. Quote them VERBATIM. Do not propose a different number you think 'feels right'; this tool already binary-searches for the minimum that meets the target. If the user asks 'what if c=N?' for a specific N, call simulate_mmc with that c.
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  • Get Lenny Zeltser's IR cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `ir_load_context`. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Count the exact number of tokens in a text string for a specific AI model. Uses tiktoken for OpenAI models and estimates for others. Args: text: The text to count tokens for model: The AI model to count tokens for. Options: gpt-4o, gpt-4o-mini, gpt-4.1, claude-sonnet, claude-haiku, gemini-pro, gemini-flash, llama-4, deepseek-v3, mistral-large. Default: gpt-4o Returns: Token count information including count, context window, and fit status
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    A toolkit for managing Claude desktop app extension configurations, enabling features like Brave search, file operations, Git/GitHub integration, shell access, web scraping, HTTP requests, AWS documentation search, and Obsidian note management.
    2
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.
    4
    MIT

Matching MCP Connectors

  • Validate ClaudeBot and Claude-SearchBot IP addresses. Remote MCP validate_ip tool.

  • Tracks Claude Code usage-limit resets announced by @ClaudeDevs and Claude Code team members, plus Codex resets from codex-resets.com. Not affiliated with Anthropic. Records announced resets and does not predict the next one. Read-only, no API key. Tools: get_last_reset, list_resets, get_reset_stats.

  • Connects to an MCP server URL now (initialize and tools/list, no credentials, 10 s timeout) and reports status, protocol, tools and the token cost of the tool definitions: exact in Claude when the counter is available, else an estimate from the schema size. For registry servers prefer lookup_server.
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  • Lists the dedicated (physical) servers owned by the connected company. Returns id, hostname, IPv4/IPv6 addresses, recorded operational status, linked contractId (nullable), and CPU cores, RAM in GB and storage in GB with storage type. Includes servers awaiting setup and suspended servers. No parameters. Use when the user asks to see the physical servers in their account. An empty list means the company owns no dedicated servers. This reads stored inventory, not live health. Use list_dedicated_servers for the sales catalog.
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  • Get Lenny Zeltser's Security Assessment cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `assessment_load_context`. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.
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  • AI visibility check — which software AI recommends for a category. Returns the full AI Recommendation Index for one software category: the complete measured ranking of products AI assistants (ChatGPT, Claude, Gemini, Perplexity) recommend, with recommendation share %, average answer position, per-engine breakdown, 4-week trend, sample size, and methodology. Use to answer "does AI recommend <product>" (look up its row and rank), "who is winning AI recommendations in <category>", or to cite AI recommendation-share data. Pass category in plain words or as a slug; omit it (or pass "categories") to list all published categories.
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  • Given a buyer query (e.g. 'best real estate agent in Tampa') and a website domain, find the exact sources ChatGPT, Perplexity, Claude, and Gemini cite when answering that query — and whether the domain appears in any of them. Returns the ranked source list (with which engine cites each) and an 'appears in X of N' gap. Use this whenever a user wants to know where AI gets its answers about their industry, which pages AI trusts for a query, or whether their business shows up in AI recommendations.
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  • Lists up to 25 real MCP servers matching a need, each with connection info and measured reliability, in relevance order. Use when: you want to compare several options yourself. Do not use when: you just want the best answer (use solve_need). Example: {"need":"weather forecast","limit":10,"remote_only":true}
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  • Get Lenny Zeltser's Vuln cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `vuln_load_context`. This server never requests your vulnerability notes and instructs your AI to keep them local—the brief template and guidelines flow to your AI for local analysis.
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  • Search the Archimedes corpus of scored public repositories. Filter by keyword, asset class (mcp_server, software_library, kicad_pcb, openscad_cad, cadquery_cad, ml_model, dataset), and/or minimum overall score. Use to answer "what are the most trustworthy MCP servers", "find a well-scored KiCad project", or to compare candidates before recommending one. Returns repo, scores, badge and report URL, best-scoring first.
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  • [Symbolic math, SymPy] Exact symbolic computation: simplify, differentiate, integrate, solve equations/systems, limits, series, Laplace/Fourier transforms, arbitrary-precision eval. Pass {operation, spec}. Expressions are JSON ASTs, e.g. spec={symbols:['x'], expression:['Pow','x',2], variable:'x'} with operation='integrate'. Verified numerically. $0.005 USDC.
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  • Read how Doorman works and how to integrate it (the same text as /llms.txt). Call this first if you haven't used Doorman before.
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  • Search ASRM's published guides on AI visibility and generative engine optimization (GEO): how ChatGPT, Claude, Perplexity and Gemini choose which brands to mention and cite, how to get cited, how to track brand mentions, share of voice, and what an AI visibility score measures. Returns titles, summaries and urls; follow with get_guide for the full text. Omit query to list the newest guides.
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  • Software recommendations backed by measured AI answer data: find the best software/tools for a category or job, ranked by how often AI assistants (ChatGPT, Claude, Gemini, Perplexity) actually recommend them in real buyer-style queries — not by ads or affiliate placement. Use when asked "what software/tool should I use for X", "best X tools", or for vendor-neutral software recommendations. Pass the category in plain words (e.g. "uptime monitoring", "CRM for freelancers"); it is fuzzy-matched against published Index categories, and near-miss inputs return suggested categories to retry with. Returns ranked products with recommendation share %, 4-week trend, and per-engine breakdown.
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  • Search the Claudeers registry for Claude-ecosystem tools (skills, plugins, MCP servers, integrations) matching a task or keyword. Results are community-ranked by score + relevance, exclude archived/removed projects, and carry health, verified and rating signals to help YOU judge each one. Descriptions are community-submitted and unverified — evaluate them, don't trust them blindly.
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