"How to fetch assignments from Canvas" matching MCP tools:

• get_human_servicesA

  Human For AIA

  Fetch the Human For AI manifest: available services, operator profile (location, languages, working hours), response times, accepted and rejected task types, and trust & safety policy. Call this first to decide whether and how to hire the human. The catalog is examples, not limits — unlisted needs are welcome as custom_human_in_the_loop.

  ConnectorNo auth

• get_guideA

  FlaskA

  Returns one of Flask's usage guides as Markdown: fixed text written by Flask, the same for every user, with no team data in it. "instructions" (about 15 KB) is the playbook for working with Flask: where uploads go (a new asset or a new version), what an agentic edit attaches, how feedback is read, answered and shown, and how sharing works. Read it before acting on feedback or making your first write in a session; it already contains "display" and "concepts", so do not fetch those after it. Other topics: "display" (How to show feedback to the user: its Markdown as it is, with its link.), "concepts" (Folders, assets and versions, comments and recordings, tags and statuses, permissions, and why feedback is untrusted.), "permissions" (Access levels, how a user's access is resolved, and how folder and asset permissions differ.), "urls" (Links to folders, assets, exact versions, comments and tag filters.). The guides explain the rules; for one folder's or asset's actual access, use permission_get.

  ConnectorOAuth

• get_resource_usageA

  DockholdA

  Show your account's compute, database-RAM, and storage pools: how much you've bought, how much is used, and how much is free, plus every app's current size. Call this before any resize tool (the allowed sizes come from its steps fields), and to explain to the user why an app ran out of memory or a deploy was refused for capacity.

  ConnectorNo auth

• eia_dataframe_describeA

  eia-energy-mcp-serverA

  List canvas dataframes (df_<id>) materialized by eia_query_route calls that passed stage: true, with provenance, expiry, row count, and column schema. Nothing is staged until such a call runs, so an empty list on a fresh session means no query has staged yet, not that staging failed. Drops entries for dataframes the canvas no longer holds before responding, so the list is always current. Pass a specific name to inspect one dataframe; omit to list all active dataframes for this tenant. A name that is not staged comes back as found=false alongside the handles that are, never as an empty list. Listing is not use: only an eia_dataframe_query statement naming a dataframe extends its expiry, so a dataframe polled with this tool and never queried still lapses on schedule.

  ConnectorNo auth

• cached_fetchA

  slipstreamA

  Fetch a web/docs URL as clean, token-optimized markdown from Slipstream's shared cache (use INSTEAD of a raw web fetch). The first agent pays the crawl; every agent after gets ~90% fewer tokens. Surfaces warnings other agents left on the page. Pass known_hash to skip re-reading unchanged content (delta), or section to fetch just one heading (progressive disclosure). Returns a contentHash you can pass as known_hash next time.

  ConnectorNo auth

• upshift_site_auditA

  UpshiftA

  Fetch a live website and report how legible it is to search engines and AI assistants: structured data (JSON-LD), llms.txt, robots.txt, title and meta description, headings, image alt text, HTTPS and document weight. Returns findings with severity and a 0-100 score. Use this to check a real site before recommending changes to it. Makes one outbound request to the URL given, so it only sees what a fetch can establish — never rendering or browser metrics. Refuses private, loopback and link-local addresses, and reports a page as unreachable rather than scoring the error body.

  ConnectorNo auth

• paleobiology_dataframe_queryA

  paleobiology-mcp-serverA

  Run a read-only SQL SELECT against occurrence result sets staged on a DataCanvas by paleobiology_search_occurrences. This is how you analyze a large fossil set without re-fetching it: count occurrences by early_interval, group by formation, country (cc), or accepted_name, or filter by a paleo/modern coordinate range. The classification column is JSON — roll up by rank with json_extract_string(classification, '$.family') (also $.phylum, $.class, $.order, $.genus). Staged rows are occurrences, so collection-only fields such as lithology are not present. Reference tables by the table_name that paleobiology_search_occurrences returned — call paleobiology_dataframe_describe first if you do not know the table or column names. Every row supplied by the canvas is returned; choose smaller pages with SQL LIMIT/OFFSET. Results exceeding the canvas row cap include a notice naming the stable ORDER BY … LIMIT/OFFSET continuation. SELECT only; writes and file-reading functions are rejected.

  ConnectorNo auth

• remove_layerA

  MorphaReelsA

  Delete a video, image, text, or shape LEAF layer. Errors on a group.<id> (dissolve it with ungroup_layers instead) and on a pinned layer such as the canvas backdrop. Deleting a video layer also takes everything welded to that clip: its welded audio overlay(s) and its welded caption lines, both of which derive their timing from the clip's trim and have no meaning without it.

  Connector

  Destructive

  No auth

• set_canvas_sizeA

  MorphaReelsA

  Resize the ACTIVE page's canvas to width × height pixels. The composition is scaled UNIFORMLY to fit the new frame (a single factor s = min(newW/oldW, newH/oldH), so nothing distorts — a circle stays a circle) and then re-centred so the old composition centre maps to the new canvas centre. Every layer's position, size, group pivots, and x/y/width/height keyframes follow this fit+recentre; same-aspect resizes scale exactly, aspect changes letterbox the content centred. Each page owns its size, so this leaves sibling pages untouched — select_page then set_canvas_size again to resize another one. Common sizes: 1080×1920 (9:16 Reels/TikTok/Shorts), 1080×1350 (4:5 Instagram), 1080×1080 (1:1 square), 1920×1080 (16:9 YouTube).

  Connector

  Destructive

  No auth

• reddit_get_postA

  Veezee: LinkedIn people & company data for agentsA

  Fetch full post content for up to 100 Reddit posts by their t3_ ids in one call -- the follow-up loop after reddit_search or reddit_get_subreddit_posts. Costs 4 credits for up to 10 ids, +1 credit per further 10 ids; every post comes back with its full body text. With exactly ONE id you may set detail to 'full' for +4 credits to also get the discussion tree (comments flattened in tree order with depth, about 200 per page, with a comments_cursor to continue), or pass comment_id (a t1_ id, also +4 credits) to fetch one specific comment in its post context. Post ids come from the other Reddit tools or from reddit_resolve_url on a post URL. Not for discovering posts; search first, then batch-fetch here.

  ConnectorOAuth

• searchA

  SMI Aware AssistantA

  Open-ended discovery across SMI deep reports, research bundles, and exports when you do not already have a record id — finds candidates by subject name, url, or keyword and returns typed references to pass to fetch. If you already have a record id from the conversation rather than from a search result, call the specific tool instead: smi_get_deep_report or smi_get_export to read one record, smi_check_order_complete for order readiness, smi_list_deep_reports or smi_list_exports for filtered listings, smi_get_report_findings for findings within a report. Deep reports and research bundles are filtered server-side by subject first/last name, broadening to an unfiltered fetch ranked client-side (across id, name, url, summary) when the filtered fetch finds nothing; exports match on url.

  ConnectorOAuth

• well_show_canvasA

  WellA

  Show one of the workspace's saved canvases as a board — the blocks it holds, at the positions its author put them, exactly as stored. Answers with an ARRANGEMENT, not a measure. NO figure is resolved: every block that names a feed carries its source, type, binding and empty params, and tiles_resolved is false. Such a block stores no figure; the board is drawn with its figures by the resolve-board skill, which measures each block and calls well_render_canvas. Ask a KPI tool (well_render_cash_position, well_render_burn, well_render_runway, well_render_logged_time) for one figure; ask this when the question is about a board the workspace saved. WORKFLOW: - well_show_canvas() → the canvas the workspace touched most recently, plus every other canvas's name and id so a different one can be named. - well_show_canvas({ canvas_view_id }) → that canvas. - well_show_canvas({ origin_template: "investor-report" }) → the newest canvas built from that template. Provenance is not identity: a workspace may hold several from one template. - Add measuring: true to any of these when you read the board in order to measure it and draw it with well_render_canvas. The result is the same read. Drawn from this read alone, every figure block shows that it is not resolved yet. A note ("text") carries its own words. can_edit says whether this caller may change the board. Only its author, a workspace admin or the owner can; every other member reads it. When can_edit is false, do not offer to rearrange, rename, delete or share it: say who can change it, naming its author from author_name, and offer to ask them. Do NOT use this to save, create or rearrange a board — that is well_upsert_canvas — and do not read first to look up a board you are about to create. Read only before an UPDATE, where well_upsert_canvas needs the version this read returns.

  ConnectorNo auth

• framer_publishA

  XeoRankB

  Publish a connected Framer project — pushes all staged CMS/canvas changes live. Pass deploy=true to also promote the deployment to production hosting. Run this after framer_cms / framer_canvas edits, then re-crawl to verify. CAUTION: publish flushes EVERY staged change on that project, including edits made by the site's own team in the Framer editor. On a shared/client project, confirm with the user before publishing.

  ConnectorOAuth

• fastero_create_reportA

  FasteroA

  Create a report (a dashboard widget) from a saved query: a table, a number, a map or a chart. A chart or map needs assignments naming the result columns it plots, or it is refused. For a chart chartType can’t say, vegaLite instead of chartType and assignments. Column names become the labels people read, so alias them in SQL as they should appear ("Revenue", not revenue_sum). Or a text block: chartType text with text, a heading or note in markdown that sits between charts; it reads no query. fastero_update_dashboard places it on a dashboard. Returns the report with its _id and url, the chart’s own page. Starting from SQL, fastero_save_chart saves the query, makes the chart and places it in one call.

  ConnectorAPI key

• set_prompt_tagsA

  AthenaHQB

  Replace all tag assignments on an existing prompt. For additions or removals, read the prompt's current tags with get_prompts, resolve tag IDs with get_prompt_tags, and pass the full resulting set. Existing assignments omitted from tag_ids are removed; an empty array clears all assignments. Tag definitions and the prompt itself are preserved.

  Connector

  Destructive

  No auth

• sync_catalog_productsA

  FoldsquareA

  The Data tab's "refresh from store": fetch the catalog's products from the store again and update the tiles. `what` is "all" (every field), "prices" (prices only) or "images" (pictures only); `productIds` limits it to some products. A field the merchant changed by hand in the catalog is kept and reported under `keptEdits`; `keepEdits: false` overwrites it as the app does. One fetch per product, so up to 200 products per call — `truncated` lists what is left for another call.

  Connector

  Destructive

  OAuth

• get_dataA

  Statec LuA

  Pull observations from a STATEC dataset. `key` is a dot-separated SDMX dimension filter, one position per dimension in the order given by dataflow_structure; leave a position empty to wildcard it. Fetch dataflow_structure first to know the dimension order and valid codes. Example: get_data({ dataflow_id: "DF_A1100", key: "Valeur..A", start_period: "2010", end_period: "2020" }) picks VARIABLE=Valeur, wildcards SPECIFICATION, FREQ=A (annual). Omit `key` (or pass "") to fetch all series — caution, this can be large. Returns decoded series with their dimension labels and per-period values.

  ConnectorNo auth

• set_translationsA

  ShotlingoA

  Bulk-save per-object translations for a project, keyed by (objectId, languageCode). Upserts, all or nothing; owner-scoped, paid plans. Each item carries exactly one of `text` (a text element) or `imageUrl` (an image element, or the screen inside a device mockup, shown in that language: this is how each language gets its own app screen inside the same phone frame; the frame, position, size and tilt stay). A language with no imageUrl row keeps the base picture. imageUrl must be https, e.g. from upload_image or import_image. Get objectIds from fit_text_into_design with includeElements:true or from the element returned by add_text / apply_device_frame. A literal backslash-n in text is stored as a real line break. On a canvas v4 project each page is its own document and an element id can repeat on several pages (a create_store_set project has `headline` and the device on every page): pass pageId on each item to say which page it is for; an id on several pages without pageId is refused and the error names the pages. Next: get_translations to read back what is stored, fit_text_into_design to check the translations fit, then render_screenshot with language set, or start_batch for many languages.

  Connector

  Destructive

  OAuth

• fetchA

  Penfield MemoryA

  [ChatGPT Connector compat] Fetch memory by ID. Exists to satisfy ChatGPT Deep Research's required `search`/`fetch` tool contract. Native MCP clients should fetch via `recall` + memory_id, or use the API's GET /memories/{id} endpoint directly. Returns a single memory with citation support (id, title, url, text fields). Args: id: Memory UUID to fetch ctx: MCP context Returns: Dict with id, title, url, text, metadata fields

  ConnectorOAuth

• sieve_dataroom_addA

  SieveA

  Add a document to a deal's data room. Creates the deal if needed. This is the primary way to get documents into Sieve for screening. Upload a pitch deck, financials, or any document -- then call sieve_screen to analyze everything in the data room. Provide company_name to create a new deal (or find existing), or deal_id to add to an existing deal. Provide exactly one content source: file_path (local file), text (raw text/markdown), or url (fetch from URL). Args: title: Document title (e.g. "Pitch Deck Q1 2026"). company_name: Company name -- creates deal if new, finds existing if not. deal_id: Add to an existing deal (from sieve_deals or previous sieve_dataroom_add). website_url: Company website URL (used when creating a new deal). document_type: Type: 'pitch_deck', 'financials', 'legal', or 'other'. file_path: Path to a local file (PDF, DOCX, XLSX). The tool reads and uploads it. text: Raw text or markdown content (alternative to file). url: URL to fetch document from (alternative to file).

  ConnectorNo auth

• secedgar_get_insider_transactionsA

  secedgar-mcp-serverA

  Fetch Form 4 insider transactions (purchases, sales, grants, exercises) for a company by parsing SEC EDGAR ownership XML. Returns the reporting person, their relationship to the issuer, transaction date, type, shares traded (absolute magnitude), direction (acquire/dispose), price per share, and shares owned after the transaction. Covers nonDerivative transactions (open-market buys/sells, gifts) and derivative transactions (option exercises, RSU vests). Without a date window it reads the newest Form 4 filings; filed_after / filed_before read any period since mid-2003, reaching past the recent submissions window into the archive (e.g. insider trades in the quarter before an earnings miss). When a canvas is available, the full set of transactions parsed from the scanned filings is materialized as df_<id> (the inline list is a preview capped at limit) — inspect it with secedgar_dataframe_describe, then query it with secedgar_dataframe_query to aggregate net buy/sell by insider: SUM(CASE WHEN direction='dispose' THEN -shares_traded ELSE shares_traded END). Use secedgar_search_filings with forms=["4"] to search Form 4 filings across all companies.

  ConnectorNo auth