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472,991 tools. Updated 2026-08-24 08:51

"A tool or process for testing a dashboard" matching MCP tools:

  • Give honest usage feedback on an IA-QA MCP tool. Provide a score (1-5) and a comment. Rate low (1-2) if the tool was wrong, irrelevant, or a poor fit; rate high (4-5) only if it genuinely solved your need. Ratings are aggregated on a public dashboard at /devtools/mcp-ratings. Skip rating routine successes — we want signal, not praise. Example: rate_tool({ tool_name: "format_json", score: 2, comment: "Tried to pretty-print a JSON5 file, it rejected trailing commas — not usable for my case." })
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  • Check what is set up so far and what to do next to get building. Reports engine_connected / github_connected / project_count / payment_status and a `next_action` string you should follow VERBATIM, polling this tool between steps. `next_action` is "call_tool" (call the tool named in `next_tool`, following `next_step`) until onboarding is complete, then "done". (`next_action_detail` echoes the pre-2026-07-29 dict shape and is DEPRECATED — it is removed 2026-10-29; read next_action/next_tool instead.) - engine step: send the user the dashboard /login link. Engine subscriptions (Claude / Codex / GLM) are connected in the DASHBOARD for security — NEVER ask for or paste engine credentials in this chat. - github step: call connect_github() for an install link. - project step: create_project(...) for a new repo, or import_project(repo_full_name) for an existing one. - launch step: poll get_provisioning_status(project_id) until ready. Re-checking is YOUR job — the server does not push. Also returns a `usage` block (pool / daily / machine-hours counters + tier caps) for capacity-aware automation clients.
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  • Turn a Fix or Stop verdict into the change plan that could earn a re-score, with pillar targets, named plays, owners, stop conditions, cost of waiting and a deadline. CALL THIS after score_initiative returns Fix or Stop, using the same five context fields and any scores or work-architecture evidence from that call. Do not use it to produce the initial verdict, sequence several initiatives or diagnose measured process waste; use score_initiative, sequence_portfolio or diagnose_process for those jobs. Do not call it for Accelerate unless a specific delivery risk needs testing before commitment. resistance_type selects the will or skill route, risk_type selects the regulatory, reputational or operational route, and omitted diagnostics remain provisional with the next question returned. Lead with binding_constraint, surface honest_stop when present, and use rescore_gate to decide whether this remains Fix or becomes Stop. Pure deterministic calculation, no network, auth or side effects.
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  • Resolves a brand_job_ref returned by brand_guideline_specify when its race-to-complete window elapsed before generation finished. Read-only, in-process lookup -- never re-runs generation. Returns {"status": "processing"} if still running, {"status": "complete", "brand_ref": ..., "project_id": ..., "recommended_candidate_id": ..., "candidate_count": ...} once done (a compact summary -- use the returned brand_ref with brand_guideline_select/brand_guideline_pdf/brand_guideline_claims for full detail, the same pattern every other Brand Standard tool already uses), or {"status": "failed", "error_code": ..., "message": ...} if generation genuinely failed server-side. An unknown or expired brand_job_ref returns a structured BRAND_JOB_NOT_FOUND error, never a crash or empty success.
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  • Render a saved widget as a PNG chart, upload to GCS, and optionally return the binary image inline. Use when the user wants to see a visual snapshot or embed an image in a chat reply. Applies the same dashboard conditionsCel merge as get_dashboard_widget_data. Returns imageUrl (GCS PNG). By default also returns the PNG bytes as a base64 image block (set includeBinaryImage: false to skip binary if the payload is too large). No separate share URL — the widget already lives on the dashboard; link to the dashboard if the user wants the live chart. Does NOT work for text or table-only widgets (returns UNSUPPORTED_WIDGET). EXAMPLE: "Share my EC2 cost widget as an image" (after get returned widgetId "wid_123") → { dashboardId: "clx9abc", widgetId: "wid_123" }
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  • Update an existing dashboard's shared `dashboardContext`, widgets, tags, and/or team. Call get_skill with skillId: "dashboards" first — see skill for inheritance rules. Look up the dashboard id via search. Pass `dashboardContext` as a partial patch to edit the global filter (`conditionsCel`), period, groupBy, metricId, currency, or scopeId without recreating the dashboard — omit fields you want to keep; empty `conditionsCel` clears the filter. The legacy `context` alias is temporarily accepted but deprecated; never send both. Pass `operations` to add/replace/remove widgets. Pass `tags` to replace the full tag list (existing IDs from list_tags and/or `{ name, color? }` for new tags; `[]` clears). Pass `teamId` (from list_teams) to assign a team, or `teamId: null` to detach. At least one of `dashboardContext`, `operations`, `tags`, or `teamId` is required. Response includes `inheritedContext` so new chart widgets can omit fields matching the dashboard. Chart widgets inherit metricId, groupBy, currency, period, and conditionsCel by default — only pass per-widget overrides. Text widgets: `{ type: "text", title, textContent }`. Do not repeat from/to, datePreset, or groupBy when they match the dashboard context. Set `extendDashboardConditions: false` only when a chart widget must ignore the dashboard filter. Optional grid fields on add: `x`/`y`/`w`/`h` (from get). Returns a URL — you MUST include it in your response. EXAMPLES: see skill dashboards Workflow B (widgets) and Workflow D (context / global filter). • "Tag the AWS dashboard as infrastructure" (after list_tags returned tag id "tag_abc") → { dashboardId: "clx9aws", tags: ["tag_abc"] } • "Move the K8s dashboard to the infra team" (after list_teams returned id "team_xyz") → { dashboardId: "clx9k8s", teamId: "team_xyz" } • "Remove the dashboard from its team" → { dashboardId: "clx9k8s", teamId: null }
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Matching MCP Servers

  • F
    license
    Not graded
    quality
    C
    maintenance
    Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.

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  • Get ranked, purchasable offers (price, ETA, preview image) for fabricating a physical item from a design file. process=fdm_print for 3D printing a model (STL/OBJ/PLY/3MF/AMF/STEP/IGES), process=cnc or process=sheetmetal for machined/bent metal parts (STEP, IGES, DXF), process=decal for stickers/decals from artwork (any common image or design file — PNG/JPG/HEIC/TIFF/GIF/BMP/WEBP/AVIF/SVG/PDF/AI/EPS/PSD/CDR, auto-converted). A .ufp file (UFP part container: the design plus saved spec/constraints in one) is accepted anywhere a design file is — its saved intent applies automatically and anything the user states now wins. If the user just drops a file and asks for a price, omit process — UFP routes it. Provide the design either as design_file (an image/file the user attached or you generated — preferred) or file_url (a public URL). REORDERS: if the user has a UFP part number (from a receipt email or a previous session, looks like UFP-… or part_…), pass it as part_number INSTEAD of any file — the stored design and spec are reused and re-shopped across all current vendors. Locked parts additionally require share_key (from the owner's share link). Returns offers across vendors like Google Flights returns flights.
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  • Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.
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  • Resolves a brand_job_ref returned by brand_guideline_specify when its race-to-complete window elapsed before generation finished. Read-only, in-process lookup -- never re-runs generation. Returns {"status": "processing"} if still running, {"status": "complete", "brand_ref": ..., "project_id": ..., "recommended_candidate_id": ..., "candidate_count": ...} once done (a compact summary -- use the returned brand_ref with brand_guideline_select/brand_guideline_pdf/brand_guideline_claims for full detail, the same pattern every other Brand Standard tool already uses), or {"status": "failed", "error_code": ..., "message": ...} if generation genuinely failed server-side. An unknown or expired brand_job_ref returns a structured BRAND_JOB_NOT_FOUND error, never a crash or empty success.
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  • Submits a demo request. The prospect receives a confirmation email and must click the link in it before the request reaches a human at A Cloud Frontier. Use only when a real person has explicitly asked for a demo and provided their own working email address. Do NOT call this for testing, evaluation, or crawling purposes — automated and unconfirmable requests are rejected.
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  • Return a short, human-readable walkthrough for testing this server: the endpoint, the tool/prompt/resource names, and ready-to-paste sample prompts. Use to give someone a guided demo. For the full machine-readable capability catalog, use list_capabilities instead.
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  • The curated buyer-intent collections (e.g. mcp-servers, testing-qa, browser-automation). Use get_collection for the ranked tools inside one.
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  • ANSWER a buyer question in ONE call: which tool is best at a specific capability, with proof. Returns the resolved verdict our testing team's evidence supports — a named winner FOR THE ASKED CRITERION, every tested tool ranked with a comparable score /5, the CONDITIONS each result holds under (e.g. 'clean tables yes; nested headers no'), dissenting observations preserved as openable links, the tie-break reason, and artifact proof URLs. Answers are materialized from the evidence substrate — the same question returns the same answer. Honestly refuses (coverage: not_tested) when we never tested the topic. Start HERE for any 'which tool is best at X' / 'A or B for X' question; use get_evidence for the raw cells behind it.
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  • Publish (share) a Duvo Pulse dashboard to your whole team or your whole organization, or revert it to private (creator only). When publishing, set permission to 'view' (teammates see the dashboard) or 'edit' (teammates can also iterate on it); organization-wide viewers outside the team always get view-only access.
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  • Issue a presigned upload URL for a file to attach to a Duvo Pulse dashboard message (e.g. an HTML dashboard to copy, or a screenshot to match). POST the file bytes to the returned upload_url as multipart form data under the field name 'file', then pass the returned attachment_id in the attachments array of POST /artifacts/{artifactId}/messages. The agent reads the file directly from its sandbox. Files live as long as the dashboard's sandbox (about 12 hours), so upload shortly before sending.
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  • Get a legacy v1 Clarity process with process metadata, generated analysis, transformation guidance, generation progress, and captures. Use this for rows from listClarityProcesses where version=1; v2 rows should use getClarityProcess and snapshot detail tools.
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  • Validate, ground, and mint a Fixter dashboard link. Call describe_dashboards before first use — it defines the definition JSON this tool accepts. The whole dashboard is encoded into the returned URL; nobody can edit it afterwards, so this tool refuses to mint definitions that would render broken. It checks the structure (grid rows, panel roles, units, environment scoping), then executes every panel's SQL against your live data — variables resolved, placeholders substituted — and reports empty panels, legend overflows, and dead series. Errors block the link; warnings ship with it and belong in your handover message. Compose with grounded queries (run_sql) first; this tool verifies, it does not design.
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  • Get a one-click, pre-authenticated dashboard sign-in link for the owner. The engine-connect step — and any dashboard task (billing card update, a project page) — needs a signed-in browser. Because this server has already authenticated the workspace owner, this mints a single-use magic-link login token and returns a `/login?token=…` deep link: opening it signs the user straight into the dashboard (no email round-trip, no password) and lands them where onboarding left off. Send the user the returned `login_url`; it works once and expires in 15 minutes — call again for a fresh one.
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  • List the user's Zeekeo Launchpad campaigns (LinkedIn automation). Use this to find a campaign_id for zeekeo_send_message, or call zeekeo_create_campaign to make a new one. Requires the user to have connected their own Zeekeo Launchpad account. Direct them to rankparse.com/dashboard/integrations to connect it.
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  • Use this when the user asks about Johnson Bros. contact details, credentials, hours, payment methods, service area, or booking process. Do not use it for live availability or a customer-specific record.
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