AI Blocks

com.useaiblocks/libraryVersion 3.1.0

Search and load free AI skills, workflows, agents and prompts. Read-only, no sign-in.

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Responds516 msNov 14, 2026, 14:21 UTCAnswered our handshake without sign-in.

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Last checked: Nov 14, 2026, 14:21 UTC
Latency: 516 ms
Remotes responding: 1 of 1
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Hosting: Hosted outside the EU (detected)
Registry data as of: Nov 14, 2026, 21:12 UTC

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Streamable HTTP

https://useaiblocks.com/mcpResponds516 msNov 14, 2026, 14:21 UTC

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Claude Code

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

Claude Desktop and claude.ai

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Settings > Connectors > Add custom connector
Name: library
Remote MCP server URL: https://useaiblocks.com/mcp

Cursor

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

VS Code

code --add-mcp '{"name":"library","type":"http","url":"https://useaiblocks.com/mcp"}'

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Tools

22 tools

Tools of AI Blocks
	Description		Read-only	Idempotent	Open world
`advance_job`For a team job from start_job only; an engagement from start_outcome moves with advance_outcome. 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. This server keeps no copy, so there is no read or delete call: the state you hold is the record (read it from your local file; deleting that file ends the job). Every result is a host report, not proof of execution or consent.	For a team job from start_job only; an engagement from start_outcome moves with advance_outcome. 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. This server keeps no copy, so there is no read or delete call: the state you hold is the record (read it from your local file; deleting that file ends the job). Every result is a host report, not proof of execution or consent.	No	Yes	Yes	No
`advance_outcome`For an engagement from start_outcome only; a team job from start_job moves with advance_job. Apply one event to an engagement. This server keeps no copy, so there is no read or delete call: engagement.json in outcomes/<id>/ is the record (read it there; deleting the folder ends the 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 only), skip, block, reopen, next_round; a plan event during the run is a revision. autonomy (owner only) works any time. Every problem in an event comes back at once, with its field path.	For an engagement from start_outcome only; a team job from start_job moves with advance_job. Apply one event to an engagement. This server keeps no copy, so there is no read or delete call: engagement.json in outcomes/<id>/ is the record (read it there; deleting the folder ends the 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 only), skip, block, reopen, next_round; a plan event during the run is a revision. autonomy (owner only) works any time. Every problem in an event comes back at once, with its field path.	No	Yes	Yes	No
`fetch`Only for ChatGPT deep research and company knowledge: read one item by the id from search (such as skill/ad-angle-planner). Every other client: use get_item with the id from search_library. Returns 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.	Only for ChatGPT deep research and company knowledge: read one item by the id from search (such as skill/ad-angle-planner). Every other client: use get_item with the id from search_library. Returns 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.	No	Yes	Yes	No
`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.	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.	No	Yes	Yes	No
`get_approaches`Use to compare the different ways a job can be done before choosing one: source-backed approach families, methods, lenses and needed tools. Not needed to do a job (start_job picks the approach). Coverage and review gaps are reported honestly. Pass job or task.	Use to compare the different ways a job can be done before choosing one: source-backed approach families, methods, lenses and needed tools. Not needed to do a job (start_job picks the approach). Coverage and review gaps are reported honestly. Pass job or task.	No	Yes	Yes	No
`get_item`The one tool to read an item: any kind, by the id from a search_library or plan_workflow row (skill, workflow, agent, prompt, mind, AI tool or mini tool). Not for ChatGPT deep research, which reads search results with fetch. A skill comes with step_map (what goes before and after it); a workflow with its steps, handoff_check, a diagram to show and open_in_builder. 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. response_format detailed adds the full instructions (SKILL.md, or a workflow's governing instructions and step notes) or the whole record; use it before running an item. Pin revision_sha256 to the revision you chose, read required files with get_resource, and cite its url.	The one tool to read an item: any kind, by the id from a search_library or plan_workflow row (skill, workflow, agent, prompt, mind, AI tool or mini tool). Not for ChatGPT deep research, which reads search results with fetch. A skill comes with step_map (what goes before and after it); a workflow with its steps, handoff_check, a diagram to show and open_in_builder. 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. response_format detailed adds the full instructions (SKILL.md, or a workflow's governing instructions and step notes) or the whole record; use it before running an item. Pin revision_sha256 to the revision you chose, read required files with get_resource, and cite its url.	No	Yes	Yes	No
`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.	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.	No	Yes	Yes	No
`get_job_templates`For team jobs: 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.	For team jobs: 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.	No	Yes	Yes	No
`get_resource`Use after get_item to read one file from its file list (a script, template or reference), at that 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 arbitrary URLs or filesystem paths.	Use after get_item to read one file from its file list (a script, template or reference), at that 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 arbitrary URLs or filesystem paths.	No	Yes	Yes	No
`plan_workflow`Use when a multi-step job has no steps chosen yet: it finds candidate steps. Once you have step ids, in order, use prepare_workflow to check or change them; to read one ready workflow, use get_item. Results are suggestions, not a complete context-validated plan. Before calling, form a task brief from the current chat, supplied files and the user's me.md if they shared it: outcomes, formats, audience, constraints, available inputs and checks. Keep private context in the host; send focused task terms here. Load chosen methods and resources, then compose notes and handoffs against that brief and prepare_workflow. Returns a diagram you can show the user. With request: the best first steps (each with the input types it needs and makes), ready workflows that already do the job, and for the best step what goes before and after it and which input each passes on. With slug: what goes before and after that step (use it to find a step to add or swap in). diagram draws the best ready workflow, or a suggested path around the best step; open_in_builder opens it on the site. Returns compact rows (id, type, title, url, one_line, tested); load full instructions only for the chosen ids with get_item, and cite their url. Plain code; does not use a server-side model.	Use when a multi-step job has no steps chosen yet: it finds candidate steps. Once you have step ids, in order, use prepare_workflow to check or change them; to read one ready workflow, use get_item. Results are suggestions, not a complete context-validated plan. Before calling, form a task brief from the current chat, supplied files and the user's me.md if they shared it: outcomes, formats, audience, constraints, available inputs and checks. Keep private context in the host; send focused task terms here. Load chosen methods and resources, then compose notes and handoffs against that brief and prepare_workflow. Returns a diagram you can show the user. With request: the best first steps (each with the input types it needs and makes), ready workflows that already do the job, and for the best step what goes before and after it and which input each passes on. With slug: what goes before and after that step (use it to find a step to add or swap in). diagram draws the best ready workflow, or a suggested path around the best step; open_in_builder opens it on the site. Returns compact rows (id, type, title, url, one_line, tested); load full instructions only for the chosen ids with get_item, and cite their url. Plain code; does not use a server-side model.	No	Yes	Yes	No
`prepare_job_context`The first call for any named piece of work: a page, ad, email, copy, audit, analysis, plan or code. Then start_job. A goal with no deliverable named yet ("more sales") goes to start_outcome instead of both. 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 or data, the rubric and gates, and the AI defaults to avoid. No model calls.	The first call for any named piece of work: a page, ad, email, copy, audit, analysis, plan or code. Then start_job. A goal with no deliverable named yet ("more sales") goes to start_outcome instead of both. 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 or data, the rubric and gates, and the AI defaults to avoid. No model calls.	No	Yes	Yes	No
`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 AI Blocks. Nothing is sent or published.	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 AI Blocks. Nothing is sent or published.	No	Yes	Yes	No
`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 include task and relevant context to prepare an existing job. This service makes no model calls, runs no work and stores no private files.	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 include task and relevant context to prepare an existing job. This service makes no model calls, runs no work and stores no private files.	No	Yes	Yes	No
`prepare_workflow`Use when you already have the step ids, in order, and the user wants to see, check or change a workflow (swap, add, remove or reorder steps); also before showing any plan. No steps yet: use plan_workflow to find them. Quick check: send slugs, the step ids in order (from get_item steps or plan_workflow), with an optional goal and user_inputs. Returns a diagram you can show the user, step_checks (is each required input made by an earlier step or given by the user, plus swap_options for each step), suggestions with reasons (insert a step that makes a missing input, reorder by data flow, swap a step, remove a repeat), the proposed steps with all but swaps applied, and open_in_builder, a link that opens the proposal in the site's builder. Also returns an unsaved portable draft, selected skill inventory, review hash and handoff_check. Send full steps with pinned revisions instead of slugs for custom notes and dependencies. Suggestions and warnings never block the draft; show them and apply only what the user approves. Does not compose with our AI, save, execute or certify approval; an approval hash never authorizes external actions.	Use when you already have the step ids, in order, and the user wants to see, check or change a workflow (swap, add, remove or reorder steps); also before showing any plan. No steps yet: use plan_workflow to find them. Quick check: send slugs, the step ids in order (from get_item steps or plan_workflow), with an optional goal and user_inputs. Returns a diagram you can show the user, step_checks (is each required input made by an earlier step or given by the user, plus swap_options for each step), suggestions with reasons (insert a step that makes a missing input, reorder by data flow, swap a step, remove a repeat), the proposed steps with all but swaps applied, and open_in_builder, a link that opens the proposal in the site's builder. Also returns an unsaved portable draft, selected skill inventory, review hash and handoff_check. Send full steps with pinned revisions instead of slugs for custom notes and dependencies. Suggestions and warnings never block the draft; show them and apply only what the user approves. Does not compose with our AI, save, execute or certify approval; an approval hash never authorizes external actions.	No	Yes	Yes	No
`read_back_outcome_experiment`Use while an experiment from record_outcome_experiment is live (that tool registers and closes it). 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 guardrail breach at once; after the window, returns an honest verdict and the close payload for record_outcome_experiment. Budget and pause ideas come back as proposals for the owner; nothing is ever changed.	Use while an experiment from record_outcome_experiment is live (that tool registers and closes it). 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 guardrail breach at once; after the window, returns an honest verdict and the close payload for record_outcome_experiment. Budget and pause ideas come back as proposals for the owner; nothing is ever changed.	No	Yes	Yes	No
`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 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.	No	Yes	Yes	No
`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 experiments.jsonl, a learning candidate and an anonymised outcome report the owner may choose to share.	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 experiments.jsonl, a learning candidate and an anonymised outcome report the owner may choose to share.	No	Yes	Yes	No
`search`Only for ChatGPT deep research and company knowledge, which need this exact shape: results with id, title and url. Read one with fetch. Every other client: use search_library, the same search with filters and one-line summaries.	Only for ChatGPT deep research and company knowledge, which need this exact shape: results with id, title and url. Read one with fetch. Every other client: use search_library, the same search with filters and one-line summaries.	No	Yes	Yes	No
`search_library`Use to browse or look up catalogue items by keywords, job or date. Not for doing a piece of work (prepare_job_context) or a business goal (start_outcome). The search tool is the same search in the shape only ChatGPT deep research needs; every other client uses this one. Finds skills, workflows, agents, prompts, minds, AI tools and mini tools. Filters: type, job, level, tested, since (what's new). With no query, a job or since browses. Returns compact rows (id, type, title, url, one_line, tested); read only the ones you choose with get_item, and cite their url. Plain search; does not use a server-side model.	Use to browse or look up catalogue items by keywords, job or date. Not for doing a piece of work (prepare_job_context) or a business goal (start_outcome). The search tool is the same search in the shape only ChatGPT deep research needs; every other client uses this one. Finds skills, workflows, agents, prompts, minds, AI tools and mini tools. Filters: type, job, level, tested, since (what's new). With no query, a job or since browses. Returns compact rows (id, type, title, url, one_line, tested); read only the ones you choose with get_item, and cite their url. Plain search; does not use a server-side model.	No	Yes	Yes	No
`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.	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.	No	Yes	Yes	No
`start_job`Use after prepare_job_context (send from_context: true so the brief is not repeated); not for a goal with no deliverable (start_outcome). 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 server model calls or action authority.	Use after prepare_job_context (send from_context: true so the brief is not repeated); not for a goal with no deliverable (start_outcome). 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 server model calls or action authority.	No	Yes	No	No
`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 next step and the files for outcomes/<id>/, with METHOD.md (brief frame with examples, research protocol, composition and run rules). include_example adds a worked example of a good brief, research and plan. No work runs here.	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 next step and the files for outcomes/<id>/, with METHOD.md (brief frame with examples, research protocol, composition and run rules). include_example adds a worked example of a good brief, research and plan. No work runs here.	No	Yes	Yes	No

Details

Registry status: Active
Published: Nov 14, 2026
Updated: Nov 14, 2026
Website: https://useaiblocks.com/api-and-mcp⁠ (opens in a new tab)
Repository: Not given
Categories (suggested): AI modelsSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR: Not declared

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