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AI Design Blueprint MCP server

Which MCP servers are AI Design Blueprint's own, from the official registry and from asking its own domain, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.

read 2026-10-24

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Whose server it is
  • Registry namecom.aidesignblueprint/blueprintverified in the MCP registry

The registry name sits under aidesignblueprint.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.

When we asked itchecked 2026-10-24
  • Stateanswerschecked 2026-10-24
  • Tools29
  • Server calls itselfAI Design Blueprint
  • Server version1.26.0
  • Protocol version2025-06-18

On 2026-10-24 the server answered initialize and tools/list without a sign-in. First answer in 180 ms.

Should an agent connect itNot proven either way yet
  • Its tools do every use case we checked: validate an agent against the doctrine principles; grade a written spec before building from it.
  • Checked on 4 of the 7 days it takes to judge reliability.

Once connected

  • For "validate an agent against the doctrine principles", the likely first call is architect.validate.
  • For "grade a written spec before building from it", the likely first call is spec.validate.
  • me.add_evidence change data without a sign-in: anyone with the address can call them.
  • Its definitions take about 20346 tokens of context: enable only the tools a task needs.

Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.

Measured dailydaily checks: 4, the first on 2026-10-24
  • INITE MCP scoreafter a weeka score needs 7 daily checks: 4 so far
  • What an agent can do with it2 of 2 use cases
  • Answeredmeasuring4 of the 7 daily checks it takes to print a share
  • Median first answer647 ms
  • Space in an agent's context≈ 20,346 tokensthe definitions of all its tools (29), which an agent carries on every turn
  • Tool definitionsA · 100 of 100
  • Typed results29 of 29 toolsdeclared outputSchema: results come typed, read once
  • Every tool passes all six checks.

What an agent can do with it

  • can do · validate an agent against the doctrine principles
  • not sure · fix flagged findings and re-run the readiness score
  • can do · grade a written spec before building from it

Each of the product's use cases, put to Jev against this server's tool list: can an agent do it with these tools?

Worth a look

  • Tools that change data, on a server that answers without a sign-in: me.add_evidence

A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →

Tools it offers29 tools · read 2026-10-24
  • principles.list

    List Blueprint doctrine with stable slugs, titles, and clusters. The lens selects which of the three public doctrines: 'architecture' = the 10 agentic principles (default, the architect.validate rubric); 'surface' = the 8…

  • clusters.list

    List all principle clusters with their stable slugs and linked principle titles. Use this to discover which clusters exist before drilling in with clusters.get or filtering principles.list by cluster. Prefer clusters.get when you already…

  • principles.get

    Get one doctrine entry by stable slug. The lens selects the doctrine: 'architecture' = one of the 10 agentic principles (default); 'surface' = one of the 8 experience-design laws; 'spec' = one of the 8 spec-quality laws. Returns id…

  • clusters.get

    Get one principle cluster by stable slug. Returns the cluster definition, shared rationale, and the full set of member principles (slug + title) so the caller can pivot into principles.get without a second list call. WHEN TO CALL: the…

  • examples.get

    Get one curated example by stable slug. Returns title, summary, source-code links, principle coverage (the principle slugs the example demonstrates), difficulty, library/framework, and implementation notes. Use this when you already have…

  • principles.search

    Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow'…

  • examples.search

    Search curated examples by free-text query, ranked by relevance, with optional filters: principle_ids (only examples covering those principles), difficulty (beginner/intermediate/advanced), library (e.g. 'langgraph', 'openai'). Returns…

  • assets.list

    Public: list downloadable doctrine and agent asset artifacts (skill packs, rule packs, MCP setup snippets) the user can drop into their AI coding tool to import the Blueprint as native skill/rule files. Returns a list of assets with name…

  • guides.list

    List application guides that show how Blueprint principles apply to engineering challenges (security, evaluation, observability, etc.). Use this to discover which guides exist before drilling in. Prefer guides.search when the user…

  • guides.get

    Get a full application guide by its stable slug (e.g. 'security-application', 'observable-evaluation'). Returns sections, action items, and linked principles. Use this when you already have the guide slug from guides.list or…

  • guides.search

    Search application guides by free-text query, matched against section answers and action items. Use this when the user describes an engineering challenge (security review, evaluation harness, observability) and wants matching guides…

  • signals.report

    Records a value moment (e.g. review_confidence, runtime_risk_found, workflow_clarity) after a successful validate run on any lens (architect.validate, design.validate, or spec.validate) or a doctrine session. Each event stores event_type…

  • signals.feedback

    Public: records explicit free-text user feedback about the Blueprint, this tool surface, or a specific principle/example. Captures category (bug, doctrine_critique, missing_example, ergonomics, other), free-text body, and optional…

  • architect.validate

    Pro/Teams: first-pass doctrine review of agentic code/workflow against the 10-principle AI Design Blueprint doctrine. ON CLIENT TIMEOUT: DO NOT RETRY THIS TOOL. Long-running LLM call (60-180s typical); MCP clients commonly close the call…

  • design.validate

    Pro/Teams: first-pass surface-craft review of a FRONTEND artefact (component, screen, or flow) against the 8 laws of the Experience Design Blueprint. The surface-craft companion to architect.validate: where architect.validate scores…

  • spec.validate

    Pro/Teams: first-pass specification-quality review of a WRITTEN SPEC (proposal, design doc, task breakdown, or an OpenSpec-style change bundle) against the 8 laws of the Spec Quality Blueprint. The what-to-build lens of the doctrine trio…

  • architect.validate_consensus

    Pro/Teams: N-shot CONSENSUS doctrine review of agentic code. ON CLIENT TIMEOUT: DO NOT RETRY THIS TOOL. Long-running (~80-120s for N=3 parallel LLM calls); MCP clients often close the call before the server returns. Retrying re-runs N ×…

  • architect.certify

    Pro/Teams: second-pass adversarial certification of an architect.validate run that scored production_ready (A or B first-pass tier). ON CLIENT TIMEOUT: DO NOT RETRY THIS TOOL. **RECOVERY FIRST**: the run_id is emitted in the FIRST…

  • team.summarize

    Teams/Enterprise: summarises the caller's tool-usage patterns and value signals over a configurable window (default 30 days). Returns period_days, most_used_tools (call counts and average latency), value_events by event_type…

  • me.learning_path

    Authenticated: returns the caller's Blueprint learning-path state: current course slug, stage progress, certification status (Foundation, Practitioner, Capstone), Capstone track eligibility flags, and the next recommended stage. WHEN TO…

  • me.coaching_context

    Authenticated: returns stages in the caller's active course where recorded evidence is thin relative to the stage's principle requirements. Each thin stage carries the missing principle slugs + a short diagnostic so the caller can suggest…

  • me.add_evidence

    Authenticated: append a free-text evidence note to a specific stage in the caller's active course. Notes record concrete implementation observations, decisions, or artefacts that demonstrate progress through a Blueprint principle (e.g…

  • me.sessions

    Pro/Teams: list or inspect the authenticated user's Governed Sessions (GEP-M2): durable, owner-scoped containers that group validation runs across lenses (architect.validate → 'architecture', design.validate → 'surface', spec.validate →…

  • me.session_event

    Pro/Teams: append a TYPED TEAM EVENT to a Governed Session's timeline (GEP-M6). This is how the user's own harness makes trio work inspectable: handoffs between role lenses, pushbacks, plan previews, gates, and acks land as structured…

  • me.await_steer

    Pro/Teams. BLOCK until the session owner posts the next `steer` event to a Governed Session from AIDB Studio, then return it. DELIVERY GUARANTEE: the durable cursor read against the session log is authoritative (at-least-once: a lost…

  • me.validation_history

    Pro/Teams: return the authenticated user's validation run history for all three lenses (architect.validate → validator='architecture', design.validate → validator='surface', spec.validate → validator='spec') with the Blueprint Readiness…

  • handoffs.operator

    Authenticated: creates a support handoff record when an agent needs human review, account-specific escalation, or operator follow-up that cannot be resolved with the read-only doctrine tools. Persists a SupportHandoff row (reason, topic…

  • handoffs.partnership

    Authenticated: creates a partnerships handoff record for design-partner, ecosystem, training, or advisory conversations needing human review. Persists a PartnershipHandoff row routed to the partnerships inbox; the user is contacted by the…

  • handoffs.agency

    Authenticated: submit an agency engagement enquiry on behalf of the caller for a founder-led discovery call. Persists an AgencyHandoff row routed to the agency inbox; the user is contacted by the team for a scoped proposal. Engagement…

How to connect

Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:

{
  "mcpServers": {
    "blueprint": {
      "type": "http",
      "url": "https://aidesignblueprint.com/mcp"
    }
  }
}

Add it

Claude Code, in a terminal

claude mcp add --transport http aidesignblueprint https://aidesignblueprint.com/mcp

Add to CursorAdd to VS Code

claude.ai, ChatGPT and other clients: add https://aidesignblueprint.com/mcp as a custom connector in the settings.

Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.