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578,249 tools. Updated 2026-09-16 03:53

"Thinking process for developing or using Cursor AI" matching MCP tools:

  • Read one source-free operating packet: active version metadata, the latest explicitly selected observed project input, review attention, artifact index, work queue, and current activity cursor. Imported input is immutable evidence, not an AI proposal or live filesystem sync; private 2ools skills, prompts, routing, governance text, and generated version source are not returned.
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  • The front door for one AI investment decision. CALL THIS FIRST when the user describes an AI idea in ordinary language or asks whether it should proceed. It resolves industry, revenue, business function, AI tier and organisational readiness, then returns the next missing question or an Accelerate, Fix or Stop verdict. Use work_architecture to test whether the end-to-end workflow, affected roles, human decision rights and performance measures have been redesigned. A stated gap or missing work architecture evidence blocks Accelerate and stays visible in the audit trail. Pillar scores and work architecture evidence remain optional inputs, but unresolved values are never guessed and cannot unlock Accelerate. Use score_initiative when the canonical fields are already known, score_portfolio for several initiatives, and diagnose_process for measured waste in a running process. Pure deterministic calculation, no network, auth or side effects.
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  • Incremental poll: raw item-level AI news added since a cursor, oldest→newest, with a nextCursor for your next call — use this for "what's new since I last checked"; for the curated once-daily synthesis use get_daily_briefing. Omit cursor for the latest items plus a cursor to start polling from. Titles + links + topics (bodies and higher limits are on the paid tier).
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  • Quantify the annual EUR cost of an AI ambition outrunning the operating model: queues, hand-offs and slow decisions that prevent the organisation capturing the value already assumed in the case. CALL THIS when the user needs the cost of waiting for the organisation to change, or when a Fix plan needs a cost-of-waiting figure. Do not use it to score an AI initiative, estimate the implementation cost, or calculate a process saving: use score_initiative for the investment verdict, diagnose_process for a running process, and recommend_improvements for the change plan. revenue_eur sets the absolute EUR range; ai_tier and readiness together set the drag rate and pace_gap, so gen3 in a siloed organisation costs more than gen1 in an agile one. industry is accepted for a consistent interface and defaults to universal, but does not change this calculation yet. Returns a low/high EUR range, drag rate, pace-gap severity, drivers and source. Pure deterministic calculation — no network, auth, or side effects.
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  • Poll a v2 app's change feed for what has happened: row creates, updates and deletes, from any writer, agent or human. It is the long-poll analogue of `homespun apps watch`, since MCP has no streaming. The loop is: call with no `since` first, process the returned entries, keep the cursor, then call again passing it as `since` to get only newer entries. Passing wait (around 25) holds the request open until an entry arrives or it times out, which is how the feed is waited on rather than busy-polled. A `since` older than the retention floor returns resync_required, and the collections are then re-listed with list_rows. Returns { entries, cursor, truncated }.
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  • Poll a v2 app's change feed for what has happened: row creates, updates and deletes, from any writer, agent or human. It is the long-poll analogue of `homespun apps watch`, since MCP has no streaming. The loop is: call with no `since` first, process the returned entries, keep the cursor, then call again passing it as `since` to get only newer entries. Passing wait (around 25) holds the request open until an entry arrives or it times out, which is how the feed is waited on rather than busy-polled. A `since` older than the retention floor returns resync_required, and the collections are then re-listed with list_rows. Returns { entries, cursor, truncated }.
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Matching MCP Servers

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  • Connect AI agents to Process Street workflows, tasks, runs, data sets, and operational records.

  • Find relevant Smart‑Thinking memories fast. Fetch full entries by ID to get complete context. Spee…

  • Analyze any image using AI vision for manual inspection, debugging, visual description, or supplemental critique. Provide exactly one source: generation_result_id for a Shoot Board generation, uploaded_file_id for a Files item, or image_url for a public HTTPS image. Do not use this as the primary QA mechanism when the user asks to QA, quality-check, validate, review, approve/reject, or assess generated results; for QA requests use queue_generation_result_qa first, then read_generation_result_qa.
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  • Check the progress and final status of a specific AI development session using its session key. Use this to monitor an asynchronous edit until it completes, fails, or is cancelled — keep checking until a terminal state. The session key comes from dreamagent_chat or dreamagent_list_sessions and is an identifier, not a secret. Returns (actual fields): 'active=', 'run_status=', 'next_after=' (cursor for the next check), optional 'new_output:' (text produced since the last check), then either "Still working — poll again" or a terminal 'done=true' line: finished (with the final output tail), 'the edit was NOT started: <reason>' (rejected early, e.g. HTTP 402 insufficient credits), or 'stream error' (the connection to the run broke — the server-side run may still have finished; verify with dreamagent_get_edit_progress). run_status values: queued | running | cancel_requested | completed | failed | cancelled | interrupted | unknown.
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  • Check the progress and final status of a specific AI development session using its session key. Use this to monitor an asynchronous edit until it completes, fails, or is cancelled — keep checking until a terminal state. The session key comes from dreamagent_chat or dreamagent_list_sessions and is an identifier, not a secret. Returns (actual fields): 'active=', 'run_status=', 'next_after=' (cursor for the next check), optional 'new_output:' (text produced since the last check), then either "Still working — poll again" or a terminal 'done=true' line: finished (with the final output tail), 'the edit was NOT started: <reason>' (rejected early, e.g. HTTP 402 insufficient credits), or 'stream error' (the connection to the run broke — the server-side run may still have finished; verify with dreamagent_get_edit_progress). run_status values: queued | running | cancel_requested | completed | failed | cancelled | interrupted | unknown.
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  • AI Document Translator — Translate text between 16 languages using AI. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.
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  • Get events V³ is currently tracking in BREAKING tempo — fast- moving stories under near-real-time monitoring right now. Use when the user asks "what's breaking", "any breaking news", or about a developing situation. Returns an empty list when nothing is in breaking tempo (a quiet news moment), which is itself a signal.
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  • Generate a PDF or Excel document from HTML (document_content) or a URL (document_url). Exactly one of document_content / document_url is required. By default the document is HOSTED and the tool returns a { download_url } you can fetch — ideal for agents (no large binary in the response). Set hosted:false to get the raw document back as base64, or async:true to enqueue a job and poll docraptor_get_document_status. IMPORTANT: real documents consume account credits (billed). Set test:true to generate a FREE, watermarked document while developing. DocRaptor API: POST /docs.
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    Destructive
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  • Find indexed native-XGR transactions using time, value and address filters before choosing a transaction for Relation Graph or Value Flow analysis. Typical use: all native transfers in the last 24 hours above a given XGR/wei amount. Results are read-only and cursor-paginated for latest/oldest sorting.
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  • Returns Mastra (Bun) and LangGraph (Python) patterns for AI agent workflows. Call this BEFORE create_workflow / update_draft when building chatbots, tool-using agents, or multi-step LLM flows. Do not hand-roll custom agent loops — use the preinstalled frameworks.
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  • List up to 25 docket entries with full observed entry text, source citations, report scope and linked documents, newest first. Metadata entries do not imply a PDF or complete docket. Use query to search entry descriptions and list_document_types for filter values. Linked documents include a filing_url and indicate whether searchable text is available. Continue with next_cursor as cursor using the same filters.
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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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  • Set the owning team of a process in the process landscape (organization admin+). On a proposed process this accepts the proposal and creates the real process for that team; on an existing process it moves the process, its captures and its brief to another team.
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  • Post-process an EXISTING rendered video (its served mp4 URL) with the proven direct-response 'reviewer' finish and/or a film-grain pass — no AI model, ~30s, a couple of credits. pills=true composites a header pill (e.g. '10/10 would buy again'), a brand-accent sub-pill, and 3-4 green-check proof pills cascading in on the beat (YOU author the copy: header ≤40 chars, sub ≤34, each point ≤44 — concrete real benefits, never fabricated stats). grain=true applies a subtle camera-grain finish that makes photoreal AI renders look phone-shot ('less AI') — works alone or with pills. Returns a NEW video; the original is untouched.
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  • Get top citation pages in AI search results. Returns cursor-paginated page rows ordered by citation count. Pass sourceVertical to scope the list to one vertical, for example the community platforms AI cites. Returns a coverage state: an unavailable window has not been rolled up yet, so an empty list is not a measured zero.
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  • Use this read-only tool when a business owner asks "How can AI help my business?", "Where do I start with AI?", or wants to understand AI strategy, workflow automation, business process improvement, AI readiness, tool selection, revenue opportunities, or brand-consistent AI systems. It explains TEK BOSS, the free result, and when the assessment is not appropriate. It never retrieves customer data.
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