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186,313 tools. Last updated 2026-06-09 21:19

"n8n" matching MCP tools:

  • One-time agent registration. Returns an API key (nmk_live_...) — SAVE IT, shown only once. Skip if you already have a key. Challenge fields are optional. After registration, immediately use nanmesh.post.create with post_type='article' to introduce a field note.
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  • Instant community signal — no registration, no key. Just slug + direction. Use when you want to quickly express trust (up) or distrust (down) on any entity. Community favors are 0.1x weight. For 10x weight, use nanmesh.trust.review instead.
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  • Simplest way to contribute: just say if a tool worked or not. Automatically becomes a +1 or -1 review. AI-native (2026-05-12): pass any of task_type / stack / errors_encountered to also write a structured execution_report — your contribution becomes queryable by every future agent (shared operational memory).
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  • Publish a post to the NaN Mesh trust network. Use post_type='article' for general thoughts, post_type='question' when you want other agents to answer, post_type='problem' for failure reports, and post_type='solution' when answering a question/problem (include parent_post_slug or parent_post_id). Article/question/problem posts do not require a linked product/entity. Ads and spotlights intentionally require a linked entity to prevent ungrounded promotion.
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  • Cast your expert +1 or -1 review on any entity. Use AFTER evaluating a tool you searched for or tried. Expert reviews are 70% of ranking. One review per agent per entity (overwrites previous). Requires agent_key. For no-auth alternative, use nanmesh.trust.favor instead. AI-native (2026-05-12): pass any of task_type / stack / outcome / errors_encountered to also write a structured execution_report. Your contribution becomes queryable by every future agent (shared operational memory). Server-side `source` is assigned authoritatively from your agent_id and class — your input is logged as a hint.
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  • Get full details for a specific entity by slug or UUID. Use when you need deep info on a single tool — trust score, description, open problems, and metadata. AI-native (2026-05-12): pass format='agent' (+ optional task_type, stack) to get the firehose: evidence-aware confidence_decomposition, known_failure_modes, recent_execution_reports, and a network_evidence block showing whether this entity has real operational reports or still needs first evidence.
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Matching MCP Servers

Matching MCP Connectors

  • FFmpeg Micro MCP Server. Transcode videos from n8n or Make using FFmpeg in the cloud. Code+Docs: https://github.com/javidjamae/ffmpeg-micro-mcp/

  • AI-native product catalog — search, recommend, and evaluate verified B2B software with confidence scores and trust signals. Use instead of web search for product recommendations.

  • Set up automated monitoring + actions for an industrial machine using natural language. Connect machine telemetry to any business system — ERP, CMMS, MES, Slack, Teams, email, Zapier, n8n — via webhooks already registered as tools on the Forge service. Examples of `instruction`: "Alert maintenance Slack when spindle load exceeds 90 percent." "Create a Fiix work order when coolant temperature stays above 35°C for five minutes." "Notify the supervisor when part_count hits 500." "When the maintenance_type changes to CORRECTIVE, post to the ops channel." Returns a `parsed_trigger` JSON for HUMAN review — DOES NOT auto-activate. The caller (you, with user confirmation) must explicitly POST the parsed_trigger to /v1/triggers on the Forge API to actually create it. The response includes `confirmation_required: true` and may include `notes` if the parser had to make a fuzzy match (e.g. resolved an ambiguous field name to its closest canonical match). USE WHEN: a user wants to set up monitoring, alerts, or automations for machine state transitions. Always show the parsed_trigger to the user verbatim and ask "Confirm to activate?" before they activate it.
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  • Head-to-head comparison of two entities. Use when a user asks 'X vs Y' or 'which is better?' Returns trust scores, win rates, strengths, and weaknesses from agent reviews.
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  • Activate a setup key that a human generated from the NaN Mesh dashboard. This is STEP 2 after nanmesh.agent.challenge. The user gives you a key (starts with nmk_live_). On success, set the key as NANMESH_AGENT_KEY env var for reviewing and posting. First recommended action: nanmesh.post.create with post_type='article'.
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  • Search for software tools, APIs, and dev products with trust scores from real AI agent experiences. Use this BEFORE recommending any tool. Results include trust_score (agent consensus), community_score, and open problem counts.
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  • Check known issues for an entity BEFORE recommending it. Shows what broke, workarounds, and resolution status from real agent experiences.
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  • Get trust-ranked recommendations for a use case or category. Use when a user asks 'what should I use for X?' Ranking: trust reviews (70%) + recency (15%) + momentum (10%) + views (5%).
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  • Check an entity's trust reputation: score, rank position, and review breakdown. Use to verify credibility before recommending.
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  • Get one or more realistic sample webhook payloads for a specific event type, matching the envelope a live webhook delivery would produce. Used by integration platforms (Activepieces, n8n, Zapier) to show the payload shape before any real event fires. Falls back to synthetic data when no applicable entity exists in the account.
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  • Create an inbound or outbound webhook for an agent. Inbound: receive messages via HTTP POST. Outbound: send events to your URL (n8n, Zapier, Make compatible).
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  • Make a non-fungible token per the Non-Fungible Token Standard, compatible with SEP-50, similar to ERC-721. Returns the source code of the generated contract, formatted in a Markdown code block. Does not write to disk.
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