MCP server

ZeroWidth Workbench Official

ai.zerowidth/workbench

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Build, run and publish Workbench flows, tasks, shims and knowledge bases.

Website

At a glance

Type

MCP server

Publisher

zerowidth.ai (verified by the MCP Registry)

Status

Working at last check

Tools

61

Token cost

About 21,946 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http workbench https://api.zerowidth.ai/mcp/x/workbench

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.workbench]
url = "https://api.zerowidth.ai/mcp/x/workbench"

Gemini CLI

{"mcpServers":{"workbench":{"httpUrl":"https://api.zerowidth.ai/mcp/x/workbench"}}}

Cursor

{"mcpServers":{"workbench":{"url":"https://api.zerowidth.ai/mcp/x/workbench"}}}

VS Code

{"servers":{"workbench":{"type":"http","url":"https://api.zerowidth.ai/mcp/x/workbench"}}}

Antigravity

agy mcp add workbench https://api.zerowidth.ai/mcp/x/workbench

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"workbench","server_url":"https://api.zerowidth.ai/mcp/x/workbench","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"workbench","server_url":"https://api.zerowidth.ai/mcp/x/workbench"}

Tools

• workbench_executions_get ~348 tokens
  The flow's stack traces: recent executions with per-node timelines — what each node received, produced, how long it took, and the exact error when one failed. USE THIS when a run misbehaves instead of guessing: read the failing node's inputs/error, then propose a fix (workbench_flows_edit_text) grou
• workbench_flow_authoring_guide ~137 tokens
  READ THIS FIRST before writing or editing any raw flow orchestration JSON. Covers the document shape, the settings-vs-input-ports rule (temperature, max_tokens, tools, response_format are PORTS, not settings — constants reach ports via value nodes), exact link format, plugin links, and three complet
• workbench_flows_attach_knowledge_base ~429 tokens
  Attaches a knowledge base to an AGENT flow's draft, the same way picking it in the agent editor does: a docs knowledge base becomes a search tool the model calls when a question needs it; a tabular one also puts its tables in the prompt and adds a query tool. The flow needs a system prompt (scaffold
• workbench_flows_delete Deletes data · ~268 tokens
  Deletes a flow. Its schedules stop, guest share links die, and evals targeting it can no longer run (their binding shows flowOk: false) — check caliper_flow_performance for evals and workbench_flows_schedules_list before proposing, and prefer workbench_flows_update with archived: true when the user
• workbench_flows_edit_text ~564 tokens
  Applies ONE precise text replacement to a flow's DRAFT orchestration — Edit-tool semantics: `find` must be the EXACT current text, copied character-for-character from workbench_flows_get, and must occur exactly once anywhere in the flow (system prompts, node settings, metadata, a node's type). `find
• workbench_flows_fork ~374 tokens
  Copies a PUBLIC flow from another workspace (a template) into this one as a new draft the user owns. Identify it by its flowUuid (the id on Workbench's public template pages and in `workbench_flows_get` output); optionally pin which published version to copy. Flows already in this workspace can't be
• workbench_flows_get ~345 tokens
  One flow. Default `view: summary` lists its nodes and links so you can pick one; `view: node` with a nodeId returns that node's full settings and prompt — read THAT before workbench_flows_edit_text, and copy `find` text from it character-for-character, never from memory. `view: full` returns the who
• workbench_flows_list ~159 tokens
  Lists every flow in the active workspace the caller can see. Returns summaries (id, name, visibility, updatedAt) — fetch one with `workbench_flows_get` for the full orchestration body.
• workbench_flows_publish Sends messages · ~460 tokens
  Snapshots the flow's current DRAFT as a named published version — the version schedules (workbench_flows_schedule), guest share links (workbench_flows_share_create), public-API runs, and 'published'-stage evals execute. The draft keeps evolving after this; runs on the published side don't change unt
• workbench_flows_revisions_list ~271 tokens
  The flow's revision history, newest first: published versions carry a `version` label and note; entries with version null are draft autosaves. Use it to answer 'is this published?' (any entry with a version), to find a revision id for caliper_evals_create's flowRevisionId, or to see when the draft l
• workbench_flows_run ~393 tokens
  Execute a flow and return its outputs synchronously. Runs the draft by default; pass source:"published" (optionally a version) to run the live published version. Spends workspace LLM budget, bounded by the token's cost cap. `input` is the flow's input envelope, e.g. {"kind":"chat","messages":[…]} or
• workbench_flows_scaffold ~1176 tokens
  Creates a runnable first-draft flow from a spec you author: pick the simplest pattern that fits (classifier for read-and-bucket, structurer for transform/extract/draft-for-review, agent for genuinely conversational), write a production-quality system prompt grounded in what the user told you, and ma
• workbench_flows_scenarios_create ~379 tokens
  Saves a named scenario: values for the flow's variables, e.g. one demo customer. It shows in the test pane's Scenarios menu, and Caliper evals can run as it. Use the person's details from what the user shared (a CRM screenshot, a profile) and say which ones you made up. May return `needs_confirmatio
• workbench_flows_scenarios_delete Deletes data · ~222 tokens
  Deletes one scenario. A design session running as it goes back to no scenario. May return `needs_confirmation`.
• workbench_flows_scenarios_list ~192 tokens
  A flow's variables (each {{token}} in an agent's prompt, with its type) and every saved scenario with its values. Read this before creating or updating a scenario, so the values use the flow's real variable names.
• workbench_flows_scenarios_update ~370 tokens
  Renames a scenario or changes its values. `values` MERGES into what's saved: pass only the variables that change, and null to clear one. Get the scenarioId from workbench_flows_scenarios_list. May return `needs_confirmation`.
• workbench_flows_schedule ~1563 tokens
  Set a specific built flow to run automatically on a cadence — the deterministic counterpart to a routine. Each run executes the flow's latest PUBLISHED revision with the fixed `input` envelope and routes the output per `delivery`. USE THIS when the user wants a flow they've built to run on a schedul
• workbench_flows_schedules_delete Deletes data · ~241 tokens
  Removes a schedule for good. Prefer workbench_flows_schedules_update with enabled: false when the user might want it back. May return `needs_confirmation`.
• workbench_flows_schedules_list ~227 tokens
  Every schedule on one flow: cadence, whether it's paused (`enabled: false`), the next fire time, delivery, and the last run's status. Read this before workbench_flows_schedule (don't create a duplicate) and to get the scheduleId for workbench_flows_schedules_update / workbench_flows_schedules_delete
• workbench_flows_schedules_run_now ~339 tokens
  Runs one iteration of a schedule immediately through the real scheduled pipeline (same input, same delivery — the email or channel it normally posts to) without moving its cadence. Works on paused schedules. Use it to test a schedule the user just set up. Spends workspace credit and delivers for rea
• workbench_flows_schedules_update ~1476 tokens
  Changes one schedule: `enabled: false` pauses it (configuration kept), `enabled: true` resumes and recomputes the next fire time from now; `interval` / `scheduleTime` / `scheduleTimezone` / `scheduleDayOfWeek` change the cadence; `label`, `delivery`, and `input` can change too. Pass only what change
• workbench_flows_share_create ~354 tokens
  Creates a no-account guest link where anyone can chat with the flow's latest PUBLISHED revision at workbench's /s/<token> page — the fastest way to put a working flow in a stakeholder's hands ('here, try it'). The flow must have a published version (workbench_flows_revisions_list shows it; publish w
• workbench_flows_shares_list ~219 tokens
  Every guest link on one flow, newest first: label, whether it's still live, the shareUrl (live links only — dead ones have no URL), expiry, and how many guests and messages it has seen. Use it to answer 'who has access', to recover a link the user lost, and to get the shareId for workbench_flows_sha
• workbench_flows_shares_revoke Changes accounts · ~255 tokens
  Kills one guest link immediately — anyone holding it gets a closed page from then on. Conversations already had stay in the flow's history. Get the shareId from workbench_flows_shares_list. May return `needs_confirmation`.
• workbench_flows_update ~466 tokens
  Changes a flow's name, description, visibility, tags, or archived state — the metadata around the flow, NOT its orchestration (prompts and nodes change through workbench_flows_edit_text). Pass only what changes. Archiving hides the flow from the default gallery but leaves it runnable, scheduled, and
• workbench_kb_add_documents ~583 tokens
  Adds documents to a knowledge base and starts ingestion (chunk + embed; graph KBs also extract entities; tabular KBs load CSV as tables). Text goes inline (Markdown, plain text, CSV — encoding utf8); binary files (PDF, .docx) go base64-encoded with their mimeType. Up to 50 sources per call, ~10 MB e
• workbench_kb_create ~346 tokens
  Creates an empty knowledge base. Recipe 'docs' (default) for reference material an agent searches at runtime; 'tabular' for spreadsheet-style data queried with SQL; 'graph' for entity/relationship extraction. After creating, add content with workbench_kb_add_documents, then give an agent flow a sear
• workbench_kb_delete Deletes data · ~230 tokens
  Deletes a knowledge base and everything in it. Flows that search it will find nothing — check which agents use it (the user knows; the KB page in Workbench lists them) and say so before proposing. May return `needs_confirmation`.
• workbench_kb_document_delete Deletes data · ~263 tokens
  Removes one ingested document and all its chunks; searches stop returning it at once. Get the documentId from workbench_kb_documents_list. To replace a document, remove it then workbench_kb_add_documents the new version. May return `needs_confirmation`.
• workbench_kb_documents_list ~229 tokens
  Every document ingested into the KB's current content: id, name, type, size, chunk count. Empty for a KB with nothing ingested yet (or one whose ingestion is still running — check workbench_kb_ingestion_status). Use it before workbench_kb_add_documents to avoid re-adding a document, and to get the d
• workbench_kb_get ~188 tokens
  One knowledge base: name, recipe (docs / tabular / graph), status, document and chunk counts, embedding model, and ingestion settings. Read it to confirm a KB has content before pointing a flow at it. Get the kbId from workbench_kb_list.
• workbench_kb_ingestion_status ~259 tokens
  The state of one ingestion run started by workbench_kb_add_documents: PENDING / RUNNING / DONE / FAILED, chunks written, and the error when it failed. Read it when the user asks whether their documents are in yet, or before a search that needs them — don't poll in a loop; ingestion of a few document
• workbench_kb_list ~166 tokens
  Lists every knowledge base in the active workspace the caller can see. Returns summaries (id, name, description, status, doc/chunk counts, embedding model). Use an id with `workbench_kb_search` to retrieve content.
• workbench_kb_search ~335 tokens
  Retrieves the most relevant chunks from one knowledge base — the core RAG primitive. `mode:"semantic"` (default) embeds the query and ranks by meaning (spends a small amount of workspace credit); `mode:"keyword"` is a free case-insensitive substring match. Each hit carries the chunk text, its docume
• workbench_node_catalog_get ~429 tokens
  The ground truth for what nodes exist and what their ports actually are — verify against this instead of recalling. Search by keyword/category for summaries; pass `slug` for one node's full detail (inputs, outputs, settings). Inputs are PORTS fed by links; settings live on the node — see `workbench_
• workbench_shim_add_answer ~258 tokens
  Adds one answer (a label and, optionally, when it applies). The shim needs three examples of it before it builds again with the new answer. May return `needs_confirmation`.
• workbench_shim_add_examples ~366 tokens
  Adds example inputs to one answer. Write inputs a real person would actually type in the shim's setting — varied in length, register and specifics, each one clearly this answer and not another — never paraphrases of the answer's name. Read the shim first so new examples fit alongside the existing on
• workbench_shim_create ~389 tokens
  Creates a shim from a name, the question it answers, and its answers. Add examples afterwards with workbench_shim_add_examples — three or more per answer and it builds on its own. May return `needs_confirmation`.
• workbench_shim_get ~258 tokens
  One shim in full: the question, where its inputs come from, every answer with its description and examples, what the shim still needs before it can build, and the newest build's report — held-out accuracy, recall per answer, which answers get mistaken for which, and the compiler's notes. Read it bef
• workbench_shim_list ~181 tokens
  Every shim the user can see: id, name, the question it answers, how many answers and examples it has, and the published version's held-out accuracy (null until something is published). A shim is a small decision model that runs inside an app with no model call. Start here to get a shimId.
• workbench_tasks_act ~321 tokens
  Records THIS user's verdict on a run that is waiting on them — the labels come from the gate (workbench_tasks_run_view shows them via the plan; a wrong label errors listing the real options). Echo the verdict + note back to the user in one line BEFORE calling; that echo is the confirmation. Refuses
• workbench_tasks_compile ~352 tokens
  Runs the compiler over a sentence and returns the PROPOSED plan (or repair-grade problems — fix by refining the sentence with the user, not by guessing). Nothing persists. Present the proposal in plain terms: which clauses run flows, which you will handle, who decides, what the compiler noted. `comp
• workbench_tasks_create ~406 tokens
  Creates a DRAFT Task from a name + sentence. A Task is for work with people in the loop (someone approves, decides or acts on each item before anything else happens) or a specific process mapped in Compass; its runs are measured. When nobody but you acts on it and you'd just do the same thing each t
• workbench_tasks_delete Deletes data · ~237 tokens
  Deletes a task. Runs still in flight are stopped (a gate waiting on someone is closed), and its schedule trigger stops firing; past runs stay in history. Check workbench_tasks_get for live runs and say so before proposing. May return `needs_confirmation`.
• workbench_tasks_freeze ~335 tokens
  Freezes a reviewed plan as the Task's next version and activates it. Pass the EXACT plan object a compile returned — never hand-edit it (change the sentence and recompile instead). Freeze ONLY after the user has seen the proposal and said go; echo what you're freezing in one line first. In-flight ru
• workbench_tasks_get ~265 tokens
  One Task in full: its sentence, status, the latest saved plan (the clauses — which run flows, which the assistant handles, who decides at each gate) with the flow and people names the plan refers to, and its recent runs, plus the sites its machine may reach (allowedSites) and the sites its plan name
• workbench_tasks_list ~177 tokens
  Lists the workspace's Tasks — sentence-orchestrated processes — with their sentence, status, and recent runs (id, status, who a waiting run is on). Use this to find a task the user names ('claims intake') and to see what's in flight; workbench_tasks_get reads one in full.
• workbench_tasks_run_view ~190 tokens
  The run's current state rendered as its sentence: what ran (with timings), which path each gate took, what's waiting on whom and for how long, what's coming up. Use whenever the user asks where something stands, and after acting on a gate.
• workbench_tasks_set_sites ~343 tokens
  Sets the full list of sites a Task's machine may reach (example.com, or *.example.com for its subdomains; up to 20), for steps that have to use a site like a person would. It replaces the list, so read workbench_tasks_get first (allowedSites, and computer.sites for what the plan names) and pass ever
• workbench_tasks_start ~306 tokens
  Kicks off a run of a Task and returns at once; the run carries on by itself and is live on the task's page. When the task expects an input document (its trigger has an input), pass the user's material as `input` — pasted text, extracted attachment text, or JSON. Tell the user it has started and what
• workbench_tasks_update ~248 tokens
  Changes a task's name — the gallery label only. The sentence and plan are versioned and change through workbench_tasks_compile + workbench_tasks_freeze, never here. May return `needs_confirmation`.

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