AI Blocks

Connect Remote server

claude mcp add --transport http library https://useaiblocks.com/mcp

{
  "mcpServers": {
    "library": {
      "url": "https://useaiblocks.com/mcp"
    }
  }
}

{
  "servers": {
    "library": {
      "type": "http",
      "url": "https://useaiblocks.com/mcp"
    }
  }
}

Settings > Connectors > Add custom connector
URL: https://useaiblocks.com/mcp

Tools 25 found in our last check

• start_outcome

  For a goal or problem with no deliverable named yet, in the owner's own words ("more customers", "my ad costs are rising"). For a named piece of work, such as a page, ads, emails, an audit or a plan, use prepare_job_context. Returns a new engagement waiting for its brief, the ne…

• advance_outcome

  Apply one event to an engagement. Before the run: brief (the pinned-down outcome), plan (research and the composed plan, checked against our rules and the live catalogue), approve_plan (owner only). During the run: data, start, complete (with outputs and checks), approve (owner…

• record_outcome_decision

  Record what the owner chose, the options considered (best-ranked first), what they passed over and why. Passing over the top option needs a reason. Returns a line for decisions.jsonl and, if a durable rule was stated, a learning candidate with where to save it.

• record_outcome_experiment

  Register a test before it goes live (action register: change, metric, baseline, window, minimum volume, guardrails), then close it (action close: observed, volume, guardrail results, verdict). Low volume forces INCONCLUSIVE; a broken guardrail is never a WIN. Returns a line for…

• read_back_outcome_experiment

  Without a reading: the read-back schedule for every open experiment and a routine prompt for a host scheduler (Claude Code scheduled task or cron), set up only if the owner agrees. With a reading: compares it with the registered baseline, minimum volume and guardrails; flags a g…

• prepare_outcome_pattern

  After a finished round, returns the exact anonymised PATTERN.json the owner would share (names, figures, links and contact details removed) and its sha256. Only if the owner says yes to that file, call again with consent to get PATTERN-SUBMISSION.json for review by a person at A…

• prepare_job_context

  The first call for any piece of work: a page, ad, email, copy, audit, analysis, plan or code. Returns a short brief to act on, up to 3 questions to ask (each with a default) and whether one lead or a team fits. Also an annex to save: what to capture from the client’s real site o…

• start_job

  Decides who does a job and says why. One kind of work: one lead, with the lead to load, the questions and the rubric. Mixed kinds of work, a large batch or mode team: one lead with helpers, the short team method and a state for advance_job. All work runs in the user’s AI; no ser…

• advance_job

  Team jobs only. Send the latest complete state and state_digest unchanged, with one event and its document. Each step checks its record; a refusal names the field to fix. Artifacts stay local; send hashes. Every result is a host report, not proof of execution or consent.

• propose_team

  The roster a team job would get: one lead who owns the deliverable and the helpers it may call, matched from published roles and personas. start_job returns this for a team job. Review any unmapped catalogue gaps before accepting.

• get_approaches

  Read source-backed approach families, methods, lenses and needed tools. Coverage and review gaps are reported honestly. Pass job or task.

• get_job_templates

  JOB-METHOD.md (the short team method), JOB-RECORDS.md (every record field; open it only when advance_job refuses a record) and the delivery templates.

• get_job_preferences

  On this anonymous service, return recommended choices and a local-file template. Signed-in connections use the scoped private preference record. No private data is loaded publicly.

• set_job_preferences

  Anonymous calls only prepare local preference files; they save nothing on the server. Signed-in connections require the selected workspace write consent. An ordinary one-off request never changes saved defaults.

• find_specialist

  Find worker candidates for a deliverable. Compare their remit and outputs, then use prepare_specialist to onboard the chosen worker. Keep unrelated private context out of discovery.

• prepare_specialist

  Supply role_id only to load a complete base specialist: README, setup, SOUL, intake, playbook, handoff and best-practice files, pinned methods and a full ZIP download. The host AI asks task and output questions in the conversation; no website context form is required. Optionally…

• search_library

  Look up one item (to start a piece of work, use prepare_job_context; for a business goal, start_outcome). Find skills, workflows, agents, prompts, minds, AI tools and mini tools by keywords and intent. Filters: type, job, level, tested, since (what's new). With no query, a job o…

• plan_workflow

  Find candidate steps for a multi-step job; these are suggestions, not a complete context-validated plan. Before calling, form a task brief from the current chat, supplied files and authorized me.md (get_me when available): outcomes, formats, audience, constraints, available inpu…

• get_skill

  Retrieve a skill. Concise (default): summary, inputs, outputs, how to use, file list with hashes, and step_map (what usually goes before and after it and the input each passes on). response_format detailed adds the full SKILL.md instructions and resource links; use it before run…

• get_workflow

  Retrieve a public workflow, its declared order and skill references, plus handoff_check: which step passes each input to which, and which inputs the user gives. Returns a diagram you can show the user (Mermaid; detailed adds a text outline) and open_in_builder, a link that opens…

• get_resource

  Read one inventoried resource at an exact skill revision. Text returns bounded ordered chunks; follow next_offset until null and verify full character coverage. Binary files return a download descriptor for the host to retrieve and verify. Paths are archive-relative, never arbit…

• prepare_workflow

  Check a workflow, or a change to one. Call it whenever the user wants to see, check or change a workflow (swap, add, remove or reorder steps), and before showing any plan. Quick check: send slugs, the step ids in order (from get_workflow steps or plan_workflow), with an optional…

• get_item

  Get one item of any kind by the id from search_library: an agent, prompt, mind, AI tool or mini tool (skills and workflows work too). Concise (default): what it does, inputs and outputs, how to use it, files or links, and for AI tools the price, limits and when we last checked.…

• search

  Search AI Blocks in the shape ChatGPT deep research and company knowledge use: results with id, title and url. Read one with fetch. search_library does the same with filters and one-line summaries.

• fetch

  Read one item by the id from search (such as skill/ad-angle-planner): its full text (the SKILL.md, or the AI tool or mini tool record), url to cite and metadata. Text over 48,000 characters is cut; metadata.rest says how to read the rest.

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