"A server for orchestrating intelligent agents to solve spatial reasoning tasks in 3D environments" matching MCP tools:

• browse_tasks

  AgentMarketplace

  Browse tasks on the marketplace. Defaults to open (``posted``) tasks. Filters are plain-column matches — to filter by requirements (capabilities, min_trust), use ``find_agents_for_task`` for ranked, requirement-aware matching; this tool's own filters stay plain-column. Args: access_token: AgentAuth bearer token (requires ``market.read``). status: Task status to filter on. Defaults to ``"posted"`` (open tasks). Pass any valid status to see tasks in other states. task_type: Optional exact-match task type filter. limit: Maximum results, 1-100. Default 20. Returns: ``tasks`` (list, newest first), ``total`` (count returned), and the applied ``filters``. ``{"error_code": "invalid_input", ...}`` listing the valid values if ``status`` is not a real task status.

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• convert_from_url

  Botverse

  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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• poker.game.tasks.list

  retro

  Returns the tasks of a poker game with their estimate, individual votes, tracker key and link. needs_sync tells whether the agreed estimate still differs from the one stored in the tracker — feed those tasks to poker.game.task.sync. Filter with estimated to see what is done or what is left.

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• publish_task

  Molt2Meet

  Publish a task to make it visible to operators. Works for both settlementMode='escrow' and 'direct' tasks. The task must be in Draft or Funded status. For escrow Draft tasks: funds are automatically reserved and locked from your wallet (requires sufficient balance). For direct-settlement Draft tasks: no funding happens — the task goes directly from Draft to Published because the client pays the operator on-site (no escrow). This is the intended shortcut for direct-settlement. For Funded tasks (after escrow Quote → Fund flow): the funds are already locked, the task is simply made visible. After publishing, operators can accept the task. Requires authentication. Next: wait for task.accepted via get_task_events or webhook.

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• create_workspace

  Dock

  Create a new workspace in the caller's org. Works for both user and agent callers; agent-created workspaces attribute to the agent and enroll the agent's owning user as a co-owner so the human sees it in their dashboard. The new workspace is seeded with one primary surface matching `mode`: `doc` → a Notes tab (for prose), `table` → a Sheet tab (for records), `html` → a Mockup tab (sandboxed HTML preview). Decide the surface before you create: prose (briefs, notes, summaries, drafts) → `doc`; records with shared columns (tasks, leads, rows) → `table`. If you omit `mode`, pass `initial_markdown` to signal a `doc`; with neither `mode` nor `initial_markdown`, an agent caller gets a guided error asking it to choose `doc` or `table` (so you never silently land on the wrong surface). An explicit `mode` is always honored. `html` is only picked when explicitly requested. Add more tabs of any kind later via `create_surface`. Agent-created workspaces default to org-visibility so sibling agents in the same org aren't 403'd. For prose content (briefs, summaries, changelogs) pass `initial_markdown` to seed the doc body in one call; the markdown is converted server-side, no need to hand-build ProseMirror JSON.

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• who_query_indicator_data

  who-gho-mcp-server

  Query data rows for a single WHO GHO indicator with optional spatial, temporal, and dimension filters. Returns rows with numeric values, uncertainty intervals (Low/High), and spatial/time metadata. This is the primary data-fetching tool in the find-then-query workflow: use who_search_indicators to find the indicator code, optionally call who_get_indicator_metadata to confirm which filter dimensions are valid, then call this tool. Spatial filters are mutually exclusive per call: provide only one of country_codes, region_codes, or income_group_codes — mixing them triggers an error. Omitting all spatial filters returns all geographies (may be large; use limit to cap). The sex filter only applies when the indicator uses SEX as its first cross-cutting dimension — if not, the filter returns empty rows; check who_get_indicator_metadata first if uncertain. Rows are returned in a deterministic order (most recent first by default), so a capped result is the top of a defined slice rather than an arbitrary sample; page through the rest with offset.

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• get_dataset_info

  dynamical.org Weather & Climate Catalog

  Get documentation, spatial/time resolution, domain, and update cadence for one dynamical.org dataset. dynamical.org/catalog is itself rendered from this same STAC catalog, so this tool fetches the collection document live (short TTL cache) rather than relying on anything baked into this server -- it's always as fresh as the STAC catalog itself. Args: collection_id: A STAC collection id, e.g. "noaa-gfs-forecast", "noaa-hrrr-analysis", or "ecmwf-aifs-ens-forecast". Use search_catalog to discover ids. Returns: A dict with title/model name, prose descriptions, spatial and time domain/resolution, forecast range (for forecast datasets), license and attribution, the dataset's variables, and links to its docs page and example notebooks. Raises ValueError (listing valid ids) if collection_id is unknown.

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• import_activity

  SportsTrackLive

  Import the user's trace file (GPX, TCX, IGC, SBP or FIT, max 8 MiB) into THEIR SportsTrackLive account permanently — full analysis, 3D replay, appears in their profile with their default privacy setting. REQUIRES the user to be connected via OAuth (this MCP server supports it; the client starts the flow). For a user without an account, use create_ephemeral_replay instead. Provide the file exactly like analyze_activity_file (upload_id / file_url / file_base64).

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• decompose_product

  Pinch Grocery Prices (Australia)

  ADVANCED / single item. Do NOT use this to build a shopping list: for any list of 2 or more items, call build_basket (one call, server-side). Use decompose_product only to break ONE item into structured search attributes when you intend to override build_basket's pick for that single item. This does not call any API; it is a structured reasoning step. OUTPUT: canonical_query, disqualifiers, and suggested_category for that single item. Fill in every field based on what a typical Australian family would mean by this item. CORE RULE: Unless the user literally specifies a brand, brand_preference MUST be null and the strategy is cheapest-first (unit_price_asc, no retailer filter).

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• get_download_url

  Botverse

  Get a presigned HTTPS URL to download the completed output file. Call after get_job_status returns 'complete'. URL expires in 24 hours. NOTE: fetching this URL is a direct S3 download, which is BLOCKED in sandboxed agent environments (claude.ai, Claude Desktop, Cursor). If you are in a sandbox, use get_output_content instead to receive the bytes inline over the tool channel.

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• calculate_risk_score

  ContrastAPI

  Composite CVE risk score (0-100) — fuses CVSS, EPSS, KEV, and PoC into a single agent-ready triage signal. Formula: CVSS*0.20 + EPSS*0.35 + KEV*0.30 + PoC*0.15 (each component rescaled to 0-100 before weighting). Multiplicative boosters applied in order: KEV+PoC combo (*1.15), critical-severity-with-high-EPSS (CVSS>=9 AND EPSS>0.7, *1.10), recently published (within last 7 days, *1.05). Final score clamped to [0, 100]. Label bands: CRITICAL>=90, HIGH>=70, MEDIUM>=40, LOW<40. Urgency text encodes patch SLA (immediate when KEV; 24h/72h/30d by label). Use to triage a single CVE without orchestrating cve_lookup + exploit_lookup separately. PoC signal here is the local ExploitDB mirror only — for full multi-source exploit detail (GitHub Advisory + Shodan refs + ExploitDB), call exploit_lookup separately. Methodology adapted from mukul975/cve-mcp-server (Apache-2.0): https://github.com/mukul975/cve-mcp-server. Free: 30/hr, Pro: 500/hr. Returns {cve_id, score (0-100), label (CRITICAL/HIGH/MEDIUM/LOW), urgency, has_public_poc, components (cvss_v3, epss_score, in_kev, has_public_poc, weighted_breakdown), boosters_applied, recommendation, summary, verdict, next_calls}.

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• tm_list_scenes

  Twinmotion MCP

  Enumerate every 2D/3D view ('scene') baked into the translated model, plus a shallow dump of the model object tree (first 50 top-level nodes across all 3D views), plus the list of completed derivatives (svf2, thumbnail, obj, etc.) available via APS. The canonical discovery tool for anything downstream that needs a view name or GUID. When to use: before tm_render_image (to pick a valid camera_preset), before tm_export_video (to plan a camera path across named views), to audit what was translated ('did the 3D coordination view survive translation?'), or to expose the top-level model hierarchy for UI display. Also a useful health check — if scene_count=0, the translation is incomplete or failed. When NOT to use: not for full property queries on individual objects (this tool returns names + GUIDs + child counts only — use a dedicated property-query tool for full attribute dumps), not for geometry data (use tm_export_video for OBJ export), not on a URN that has not yet started translating. APS scopes required: viewables:read data:read. Read-only across Model Derivative manifest + metadata + object-tree endpoints. Rate limits: APS default ~50 req/min. This tool fans out across every 3D view to fetch object trees — for models with many 3D views (10+) it can burn a chunk of the budget in one call. Prefer caching the result on the caller side rather than re-invoking. Errors: 401/403 = token/scope; 404 = URN not found; 422 = n/a; 429 = back off 60s (this tool makes multiple APS calls per invocation, so 429 is more likely than on single-call tools); 5xx = APS upstream. A 202 on object-tree means APS is still building the tree — the tool retries once internally. Side effects: NONE on APS (read-only). Writes a usage_log row. Idempotent.

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• query_tasks

  cnvs.app

  Read tasks from a 'todo' board with server-side filtering — handy for 'what's overdue?' / 'what's assigned to X?' without pulling the whole board. All filters are optional and AND together: `assignee` (exact match), `priority` ('H'|'M'|'L'), `done` (boolean), `overdue` (true → due_date strictly before today, not done), `due_before` / `due_after` (ISO date window on due_date). Returns `{ boardId, mode, tasks }` — tasks ordered by sort, each with the same fields as `list_tasks`.

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• create_tasks

  Plate

  Create multiple tasks in a project in one action. Use this instead of calling create_task multiple times when the user asks to create several tasks at once. All tasks are created atomically — if validation fails for any item, nothing is created.

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• create_checkout

  IBO Studio MCP

  Create a Stripe Checkout for a package's 50% deposit. Returns checkout_url, stripe_session_id, and amount_due. Show the amount to your user and open checkout_url for THEM to approve and pay; agents never complete payment themselves. Prices are fixed server-side. Pass a stable client_request_id so retries do not create duplicate checkouts.

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• list_group_envs

  seekrit — secrets for agents

  List the environments belonging to one shared GROUP — a group holds a separate value set per slug, so its `production` differs from its `staging`. Use this when you already have a group and want its own environments; use list_envs for an application's, and list_env_groups to see which groups an application environment pulls from. Returns Environment rows with `groupId` set: [{ id, name, slug, groupId, createdAt }].

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• paywall__wallet_visa_mastercard_card_list

  Netfluid

  Returns the Netfluid wallet's tokenised Visa/Mastercards. For a card to be tokenised, one previous 3D secure transaction is required, see payment_3d_secure_link. Use wallet_visa_mastercard_recharge to charge the card. @param wallet_fk: The Netfluid wallet_fk @param pin: The Netfluid wallet PIN @return: a json object, containing the results in the "values" object

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• list_environments

  WebRun Browser Automation

  List available browser environments (persistent profiles) for this account. Returns environment IDs needed for persistent sessions in browser_task or create_session. Read-only. NOTE: workflows and agents use the connection's environment automatically — you rarely need this tool for those, and should not ask the user to choose an environment.

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• decompose_product

  Pinch

  ADVANCED / single item. Do NOT use this to build a shopping list: for any list of 2 or more items, call build_basket (one call, server-side). Use decompose_product only to break ONE item into structured search attributes when you intend to override build_basket's pick for that single item. This does not call any API; it is a structured reasoning step. OUTPUT: canonical_query, disqualifiers, and suggested_category for that single item. Fill in every field based on what a typical Australian family would mean by this item. CORE RULE: Unless the user literally specifies a brand, brand_preference MUST be null and the strategy is cheapest-first (unit_price_asc, no retailer filter).

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• create_gantt

  mcp-server

  Create a Gantt chart from a task list — no account or API key needed. YOU author the plan: list the tasks in execution order with realistic working-day durations and dependencies (0-based positions of earlier tasks; use { task, type, lag } for start-to-start/finish-to-finish links or lag). Milestones have duration 0. Only add a dependency where a task truly needs another one finished - independent tasks should run in PARALLEL (share a predecessor, or take no dependencies at all and start at the project start). Group tasks into top-level phases for a structured plan/WBS: the phase task gets isPhase: true, its tasks get parent = the position of the phase. LoopGantt schedules it with its critical-path engine and returns a picture of the chart, the dates, the critical path and a link where the user can view, export (PNG/PDF) and save the chart. Always show the user the link. Tasks with a due date take deadline: YYYY-MM-DD (a marker - the reply reports the fit). Use create_gantt when the user wants a chart to open, export or save; use schedule_project instead for what-if date math where nothing should be stored.

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