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510,001 tools. Updated 2026-09-03 15:39

"A server for managing Minecraft Fabric modpacks using Claude" matching MCP tools:

  • Who am I? Returns the signed-in account: email, @handle, plan + limits, counts of sites/domains/drives, and connected DNS providers. Call this first to orient before managing sites or domains.
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  • Find today's best time window for one kind of work, using the stored sleep history of the account this server is configured with. Returns a start and end time for the window and the projected capacity across it, tuned to the kind of work: analytical, creative, learning or administrative. Choose this tool when the user wants a slot for a task later today. Use whenpeak_performance_now for the current moment instead, and whenpeak_quick_predict when working from sleep the user describes rather than stored history. Requires WHENPEAK_API_KEY on the server and reads that one account's history, so it is only meaningful where the server runs with the user's own key. Without a key it returns a not_configured error rather than failing. Read-only and stores nothing, but each call counts against that account's monthly quota. Args: task_type: "analytical" | "creative" | "learning" | "administrative" duration_minutes: window length in minutes (default 90)
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  • Offload a document conversion to Botverse — runs server-side in seconds, returns a download link, and frees you to continue with other tasks while it processes. Use this when the source document is at a public URL — direct download links and share links from Dropbox, Google Drive, OneDrive (personal or business), SharePoint, and Box all auto-resolve to the file. If you already have the content as a string, use convert_content instead — no upload step needed. Runs entirely server-side, so it works in sandboxed agent environments (claude.ai, Claude Desktop, Cursor) — the right route there for files too large for convert_content's 4 MB inline limit. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx (tables extracted). Returns a job_id immediately. Poll get_job_status every 5s until 'complete', then get_output_content (inline, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file.
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  • Agent Brain — Reason over a question or task with your agent's own persistent memory in the loop: recalls up to 12 relevant memories from your agent's private scope, reasons with Claude, and writes up to 3 new memories back, so the agent improves with every call. Recall by meaning, not just keyword, when the estate's memory server is reachable (falls back to its own always-on store otherwise — never fails the call). Use for decisions that should build on what the agent already knows; agent-memory covers plain store/recall. Runs claude-haiku-4.5 — the response names the model that served the call; agent-brain-smart runs the identical contract on claude-sonnet-5. Input: {think: string}. Returns {answer, reasoning, confidence, memories_considered, used_memories, learned, model, engine}. (8 MESH/call, a tool · cognition)
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  • Estimate sourcing cost for a product based on fabric price, supplier pricing, and order quantity. USE WHEN: - User asks "how much would it cost to make 1000 t-shirts" - User needs a rough cost breakdown for budgeting - "ballpark cost to produce [quantity] [product] in China" - "budget estimate / sourcing cost / cost per piece for [product]" - "fabric cost + lead time estimate for [product]" - "how much to make [product] in [province]" - "rough quote / pricing range" - "can I make [product] for under $X per piece" - "多少钱 / 成本估算 / 报价 / 预算 / 做一批 [品类] 要多少钱" - "[省份] 做 [品类] 的成本大概多少" WORKFLOW: estimate_cost → optionally search_fabrics first to identify specific fabric_ids for accuracy → then recommend_suppliers for ready sources. RETURNS: { product, quantity, province, fabric_options: [{name, min_rmb, max_rmb, weight_gsm}], fabric_cost_per_meter, supplier_availability: { total_suppliers, avg_lead_time_days }, note } EXAMPLES: • User: "Rough cost to make 1000 cotton t-shirts in Guangdong" → estimate_cost({ product: "t-shirt", fabric_category: "knit", quantity: 1000, province: "Guangdong" }) • User: "What's the budget range for 5000 hoodies" → estimate_cost({ product: "hoodie", quantity: 5000 }) • User: "做 2000 件羽绒服大概多少钱" → estimate_cost({ product: "down jacket", quantity: 2000 }) ERRORS & SELF-CORRECTION: • fabric_options empty → no matching fabrics for the product term. Call search_fabrics directly with broader composition or widen the category, then re-estimate. • supplier_availability.total_suppliers = 0 → drop province filter or broaden product term. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not present the output as a binding quote — always say "estimate based on database averages, not binding". Do not try to calculate per-piece cost from fabric alone — include labor, trim, margin externally. Do not use for detailed BOM costing — use search_fabrics + get_supplier_detail manually. CONSTRAINT: These are estimates based on database averages, NOT binding quotes. Always clarify this to the user. Fabric cost is per meter (typical usage: 1-3m per piece). NOTE: Cost accuracy improves when you provide a specific fabric_id via search_fabrics first. Source: MRC Data (meacheal.ai). 中文:按面料均价 + 供应商供货能力估算 [品类] 的生产成本区间。仅供参考,非正式报价。
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  • Audit an MCP server config for risk-ranked posture findings. FREE. Flags exposed machine credentials in the config, required inputs that aren't gated/optional, unpinned versions, over-broad env access, and dangerous auto-run flags. It never echoes any matched secret value back. Typical input {"config": "<mcpize.yaml, mcp.json, or a Claude/Cursor servers block>"} returns {"posture_score": 0-100, "verdict": "...", "findings": [{"line": N, "severity": 1-5, "issue": "...", "fix": "..."}], "note": "..."}. Use on a server configuration document. Not for a skill or instruction file (audit_skill_file) and not for untrusted content an agent is about to read (injection_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
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Matching MCP Servers

  • A
    license
    B
    quality
    D
    maintenance
    Enables AI assistants to interact with and manage Minecraft servers through a standardized interface, supporting server monitoring, player management, log analysis, and command execution.
    11
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.
    2
    MIT

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  • Agent-native marketplace. Bootstrap, list inventory, search, negotiate, and trade via MCP.

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

  • Find every company a person runs or represents - across BOTH registers in one call (cross-border person search). Read-only. Parameters: - name (required): person name substring, case-insensitive, e.g. "Mustermann". - country (optional, default "all"): "AT" | "DE" | "all". - page_size (optional, default 25): results per country. - status (optional, default "all"): "active" | "inactive" | "all". Returns the merged search_companies envelope ({countries, results, per_country, notices}) plus ``person_query``; every result card carries ``country``, ``company_id`` and the matched manager. AT matches the primary managing director, DE matches all managing directors AND registered signatories. IMPORTANT: matching is by name and the registers publish birth YEAR only - a shared name across companies or countries does not prove the same person (the notice says so; use birth years and context to corroborate). For general company search use search_companies with other filters; manager_name can be combined there too.
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  • [OPEN TRIAGE / INTAKE] Submit a failure-case intake (a lightweight, semi-structured report) when no matching lesson exists, or ask a question about a knowledge gap. Low-friction entry point: No Bearer auth required — open but rate-limited; output is a GitHub issue (intake,mcp-intake,pending-review) for maintainer triage, NOT a merged lesson. For a complete, pre-structured lesson that goes straight to review, prefer misakanet_write_lesson (requires Bearer). Routing: if you are ASKING a how-to / knowledge question (not reporting a failure), set kind="question" — it opens a [Question] issue that maintainers answer/FAQ instead of scoring it as a lesson. If kind is omitted, the server auto-detects question-shaped content (no error/fix/verification + question phrasing). Returns: object {submitted: boolean, intake_id, status, redactions_applied, quality_score, receipt, routing:{kind, auto_detected}}; duplicates: {submitted: false, duplicate: true, previous_issue}. Example: misakanet_submit_intake(kind='missing_lesson', problem='pip install times out behind corporate proxy', source='claude-code'); misakanet_submit_intake(kind='question', problem='How do I configure MCP auth in production?', source='claude-code')
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  • Search the Vivid Ads catalogue by product name, category, or intended use (e.g. 'corflute', 'pull up banner', 'expo', 'shopfront'). Returns matching products grounded in Vivid's own Shopify collections, so it also surfaces same-range, same-purpose alternatives — products flagged `sameRange:true` come from the top match's curated collection (returned as `collection`). ALWAYS mention these to the customer (e.g. 'we have two Pull Up Banner options, and Fabric Banner Stands do the same job'). Treat a from-price as INDICATIVE only — use vivid_product for options then vivid_price for the exact configuration.
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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 a Stripe billing portal URL for managing payment methods and invoices. Returns a URL (not a redirect) that the human can open in a browser. Requires: API key with read scope. Args: flow: Optional. Set to "payment_method_update" to go directly to the payment method update page. Returns: {"url": "https://billing.stripe.com/p/session/..."}
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  • List all fabrics a specific supplier can provide, with quoted prices. USE WHEN user asks: - "what fabrics does [supplier name] have" / "what can this factory source for me" - "show me the catalog of supplier sup_XXX" - "what does this manufacturer offer" - "what fabric options does sup_XXX quote for denim" - "does [supplier] supply [fabric type]" - "price list / fabric catalog / offering sheet for sup_XXX" - "MOQ per fabric at this supplier" - "follow-up: 'what fabrics can they supply?' after identifying a supplier" - "[供应商] 能供应哪些面料 / 报价表 / 起订量" Returns fabric records linked to the supplier with: fabric name, category, weight, composition, and the supplier's quoted price + MOQ for that specific fabric. PREREQUISITE: You MUST have a valid supplier_id from search_suppliers or get_supplier_detail. WORKFLOW: search_suppliers → get_supplier_detail → get_supplier_fabrics → optionally get_fabric_detail (for lab-test data on a specific fabric) OR get_fabric_suppliers (cross-check price vs other suppliers for same fabric). RETURNS: { supplier_id, count, data: [{ fabric_id, name_cn, category, weight, composition, price_rmb, moq }] } EXAMPLES: • User: "What fabrics does sup_texhong_042 offer?" → get_supplier_fabrics({ supplier_id: "sup_texhong_042" }) • User: "Show me the fabric catalog and MOQs for sup_001" → get_supplier_fabrics({ supplier_id: "sup_001" }) • User: "sup_234 能做哪些面料,报价多少" → get_supplier_fabrics({ supplier_id: "sup_234" }) ERRORS & SELF-CORRECTION: • count=0 → this supplier has no linked fabric catalog in the database. Either (a) they don't self-source fabrics (CMT-only) — confirm via get_supplier_detail.ownership_type, or (b) their catalog is unmapped — use search_fabrics with their expected specialization instead. • "Supplier not found" (implicit) → the supplier_id is invalid. Re-run search_suppliers. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this for a general fabric search — use search_fabrics. Do not call to compare prices across suppliers for the SAME fabric — use get_fabric_suppliers instead. NOTE: Source: MRC Data (meacheal.ai). Prices are supplier-quoted, not binding offers. 中文:查询某供应商能供应的所有面料及其报价、起订量。
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  • List all suppliers offering a specific fabric, sorted by quality score, with price comparison. USE WHEN user asks: - "who supplies fabric fab_XXX" / "where can I buy this fabric" - "compare prices for [fabric] across suppliers" - "best supplier for [fabric specification]" - "which factory has the lowest price on FAB-XXX" - "rank suppliers by quality for this fabric" - "follow-up: 'who else sells this?'" - "source comparison for [fabric]" - "price spread on FAB-XXX" - "谁家有这块面料 / 哪个厂报价最低 / 面料供应商对比" - "[面料] 有哪些供应商 / 货源" Returns supplier records linked to the fabric with: company name, location, quality score, and that supplier's quoted price + MOQ for the fabric. Sorted by supplier quality score so the most reliable options appear first. PREREQUISITE: You MUST have a valid fabric_id from search_fabrics. WORKFLOW: search_fabrics → pick fabric_id → get_fabric_suppliers → optionally get_supplier_detail (vet the top-ranked supplier) OR compare_suppliers (up to 10 IDs from this list). RETURNS: { fabric_id, count, data: [{ supplier_id, company_name_cn, province, city, quality_score, price_rmb, moq }] } EXAMPLES: • User: "Who supplies FAB-W007 and at what price?" → get_fabric_suppliers({ fabric_id: "FAB-W007" }) • User: "Compare all suppliers for fabric FAB-K023" → get_fabric_suppliers({ fabric_id: "FAB-K023" }) • User: "FAB-123 有哪些供应商" → get_fabric_suppliers({ fabric_id: "FAB-123" }) ERRORS & SELF-CORRECTION: • count=0 → no suppliers linked to this fabric. Either (a) fabric is a spec-sheet reference with no mapped source, or (b) suppliers carry this fabric but the link isn't captured. Try search_suppliers filtered by the fabric's typical specialization (e.g. denim cluster) instead. • "Fabric not found" (implicit) → fabric_id invalid. Re-run search_fabrics. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this to browse suppliers generally — use search_suppliers. Do not call to see a supplier's full fabric range — use get_supplier_fabrics. NOTE: Source: MRC Data (meacheal.ai). Sorted by supplier quality_score DESC. 中文:查询某面料的所有供应商,按质量评分排序,含报价对比。
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  • Audit an MCP server config for risk-ranked posture findings. FREE. Flags exposed machine credentials in the config, required inputs that aren't gated/optional, unpinned versions, over-broad env access, and dangerous auto-run flags. It never echoes any matched secret value back. Typical input {"config": "<mcpize.yaml, mcp.json, or a Claude/Cursor servers block>"} returns {"posture_score": 0-100, "verdict": "...", "findings": [{"line": N, "severity": 1-5, "issue": "...", "fix": "..."}], "note": "..."}. Use on a server configuration document. Not for a skill or instruction file (audit_skill_file) and not for untrusted content an agent is about to read (injection_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
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  • Replace one incorrect identifier or attribute using the stable subject ID. The current value must match expected_value, authoritative evidence and a reason are mandatory, and the server preserves an immutable correction record in subject provenance. Use enrich_subject for missing facts; never use this operation merely to add a value.
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  • Fetches the live PostAgent agent manifest. Call this before using PostAgent in a new session, after reconnecting the MCP server, or when an installed PostAgent skill may be stale. If the installed skill is older than latestSkillVersion, read latestSkillUrl and follow those instructions for this turn; if updateRequired is true, do not perform paid or irreversible PostAgent actions until the user updates.
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  • Explain what the FXMacroData MCP server can do, which tools render MCP Apps, which tools return plain rows, what is public versus subscriber-only, and how to choose tools across ChatGPT, Claude, Cursor, Codex, and plain MCP clients. Use this when a user asks what is available, why visuals are not showing, or how to get the same result in a different interface.
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  • Retry a failed deployment using a server_token (from the failure email, the deploy-progress UI, or the dashboard). Wipes the previous broken install and runs a fresh deploy on the SAME server. Returns a new session_id — poll with check_status. Use this when the user reports a failed deploy or pastes a server_token.
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  • Fetches the live PostAgent agent manifest. Call this before using PostAgent in a new session, after reconnecting the MCP server, or when an installed PostAgent skill may be stale. If the installed skill is older than latestSkillVersion, read latestSkillUrl and follow those instructions for this turn; if updateRequired is true, do not perform paid or irreversible PostAgent actions until the user updates.
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