memi MCP server

Read from the package source without running it. The installed server may list more.

• analyze_design

  Capture a Figma node and analyze it with configured AI vision. Prereq: bridge + plugin connected; a vision-capable AI provider configured; spec-compliance mode needs the spec in the registry. Returns by mode \u2014 general: { summary, issues[], suggestions[], qualityScore }; accessibility: { summary, contrastIssues[], touchTargetIssues[], focusIssues[], wcagLevel }; spec-compliance: { summary, com

• audit_interface_craft

  Audit interface design craft from local app-quality evidence or a screenshot artifact. Returns: InterfaceCraftReport JSON \u2014 score, critique, dimensions, findings, topOpportunities (lenses: visual design, interface design, conventions, user context). Use before UI edits or after a redesign; pairs with diagnose_app_quality and audit_ux_tenets_traps.

• audit_ux_tenets_traps

  Audit UX tenets and traps from app-quality evidence or a screenshot artifact. Returns on success: UX audit JSON with score, tenetCoverage, trapRisks, findings, and recommendedTweaks. This tool does not modify source files. Use this tool: when an agent needs a focused design critique packet for clarity, feedback, control, consistency, accessibility, error recovery, progressive disclosure, workflow

• capture_screenshot

  Capture a screenshot of a Figma node (or the current page) as image data. Prereq: bridge + plugin connected (check_bridge_health); node IDs from get_selection or get_page_tree. Returns: { type: "image", data: base64, mimeType }. Feed into analyze_design; first step of the self-heal loop (CREATE \u2192 SCREENSHOT \u2192 ANALYZE \u2192 FIX). Prefer SVG for vector components, PNG for complex frames.

• check_bridge_health

  Check health of the Figma WebSocket bridge. Works with no plugin connected; never throws. Returns: { status: "healthy"|"degraded"|"down", connected, clientCount, latencyMs, uptimeSeconds, port, error? } \u2014 clientCount 0 means no plugin open in Figma. Call this first before any Figma-dependent tool.

• check_skill_compliance

  Check real source files for the objectively-checkable rules in skills/ATOMIC_DESIGN.md (composition, state, data-fetching, naming) and skills/MOTION_VIDEO_DESIGN.md (motion tokens, reduced-motion, GPU-safe properties) \u2014 a post-hoc, deterministic verification pass, the same mechanism a linter uses to enforce a style guide. This does not read the skill docs at check time or make an agent obey m

• composewrite action

  Run the agent orchestrator on a natural-language design intent \u2014 classifies, builds a multi-step plan, executes it. Prereq: Figma bridge only for Figma-touching intents. Returns: { success, plan: { steps[] }, results[], summary, errors? }; success=false with errors on failure (per-step failures do not abort the plan). Examples: "create a dashboard page with KPI cards, a chart, and a data tabl

• create_specwrite action

  Create or overwrite a spec in the registry (Zod-validated). Same-name specs are silently overwritten \u2014 check get_specs first. Returns: `Spec "<name>" saved (<type>)`. Errors: isError with Zod details on schema/JSON/type failures. Schemas \u2014 component: name, type, atomicLevel ("atom"|"molecule"|"organism"|"template"), purpose, props[], variants[], composesSpecs[] (atoms must be []), codeCo

• design_doc

  Scrape a public URL and extract its design system \u2014 parses CSS custom properties, colors, fonts, spacing, radii, shadows; the configured AI provider synthesizes a DESIGN.md. Prereq: publicly accessible URL; configured AI provider for synthesis (pass raw=true without it). Returns (raw=false): DESIGN.md with Color System, Typography, Spacing, Borders & Surfaces, Component Patterns, Voice & Tone

• design_systems_context

  Normalize design-systems-mcp corpus data into compact, deterministic agent context. This read-only tool validates caller-supplied JSON and never fetches URLs, reads files, writes files, or executes corpus content. Use mode=corpus with a native manifest plus filename-keyed entries, or mode=category with the proposed category-manifest/v1 envelope. Returns byte-capped context plus inclusion counts.

• diagnose_app_quality

  Diagnose UI quality for an existing shadcn/Tailwind app from code or a public URL. Returns on success: App-quality diagnosis V2 with scores, issues, evidence locations, affected files, confidence, effort estimates, fix categories, and app graph summary. Use this tool: before planning UI fixes, exporting a registry, or giving an AI editor context on real app design debt.

• generate_code

  Generate shadcn/ui + Tailwind code from a saved spec and write files into atomic design folders (atoms \u2192 components/ui/, molecules/organisms/templates \u2192 components/<level>/). Returns: { entryFile, files[], generatedAt, findings[], critique? }. For page specs, critique is an AI layout score (0-100) + hierarchy/spacing/consistency notes when an AI provider is configured \u2014 informationa

• generate_health_report

  Compose one self-contained design-health report (HTML + markdown) from all persisted .memoire audits \u2014 app quality, UX tenets/traps, interface craft, skill compliance, and the score trend, with provenance badges, the not-assessed legend, and the active policy hash. Prereq: run diagnose_app_quality (or the CLI audits) first so artifacts exist; missing sections are listed, never silently omitte

• get_ai_usage

  AI token usage and estimated cost for this MCP session (in-memory tracker; never throws; unknown when provider pricing is not configured). Returns: { calls, inputTokens, outputTokens, estimatedCost, knownEstimatedCost, costComplete, unpricedCalls, summary }. Use to monitor spend from analyze_design, design_doc, or compose.

• get_page_tree

  Get the hierarchical node tree of the current Figma file. Prereq: bridge + plugin connected. Returns: array of pages { id, name, type: "PAGE", children[] }; child nodes { id, name, type, children? }. IDs feed capture_screenshot and analyze_design. depth=1 pages only, 2 (default) top-level frames, 3+ component internals \u2014 high depths may be slow on large files.

• get_registry_item

  Return one shadcn registry-item.json-compatible item from the workspace. Returns: files, targets, dependencies, cssVars, and Atomic Design metadata. Errors: isError if the item is unknown (discover names via get_shadcn_registry).

• get_research

  Load and return the project's user research V2 store \u2014 observations, findings, personas, themes, quantitative metrics, and quality metadata. Prerequisites: None \u2014 reads from the local .memoire/research/ directory. Research data is populated by running `memi research from-file`, `memi research from-stickies`, `memi research from-transcript`, `memi research web`, or `memi research synthesi

• get_selection

  Get the nodes currently selected in Figma with layout/style details. Prereq: bridge + plugin connected; returns [] if nothing is selected. Returns: [{ id, name, type, width, height, x, y, layoutMode?, padding/sizing/itemSpacing?, fills?, strokes?, effects?, styles?, variantProperties? }]. Use for node IDs (capture_screenshot, analyze_design) or reading layout/variants before writing a spec. Errors

• get_shadcn_registry

  Build a shadcn registry.json-compatible index from the workspace (component specs; tokens map to a registry:theme item when present). Returns: { $schema, name, homepage, items[] } with file targets, registryDependencies, cssVars. For a single item use get_registry_item.

• get_spec

  Fetch the full body of one spec by name. Returns: full spec JSON \u2014 ComponentSpec: atomicLevel, props, variants, composesSpecs, codeConnect, WCAG fields; PageSpec: sections, meta; DataVizSpec: chartType, dataShape. Errors: isError if the name is not found (list names via get_specs).

• get_specs

  List all saved specs (cheap summary operation). Returns: [{ name, type: "component"|"page"|"dataviz"|"design"|"ia", purpose? }]; [] when none exist. Use before create_spec (overwrite check) or generate_code; fetch a full body with get_spec.

• get_tokens

  Get design tokens from the local registry, optionally filtered. Prereq: none \u2014 local read; run pull_design_system if empty. Returns: [{ name, type: "color"|"spacing"|"typography"|"radius"|"shadow"|"other", values (keyed by mode), cssVariable? }]; [] when none. format "dtcg" returns the same tokens as a W3C Design Tokens (DTCG) document instead \u2014 nested groups, $type/$value, lossless via

• measure_text

  Predict text layout \u2014 height, line count, overflow, breakpoint behavior \u2014 via Node canvas. No browser, Figma, or AI needed. Returns: { height, lineCount, lines[] }; plus { overflow } when containerHeight is given; plus { breakpoints: { mobile, tablet, desktop } } when checkBreakpoints=true. Never throws (0 height / 1 line for unparseable fonts). Use to verify labels or body copy fit fixe

• mermaid_jam_exportwrite action

  Write Mermaid Jam-ready FigJam source artifacts from research or a simulation run. This is source + open friendly: it writes .mmd/.md files under .memoire/mermaid-jam and returns next steps. It does not attempt clipboard or direct paste automation.

• plan_ui_fixes

  Build a dry-run UI fix plan from diagnosis evidence and app graph data. Returns on success: { patches[], summary, caveats[] } where every patch includes risk, confidence, affected files, operations, and writeSafe. This tool never modifies source files. Use this tool: to decide what a human or coding agent should patch before calling memi fix apply or making manual edits.

• prepare_apple_design_brief

  Prepare a compact, local-first Apple-platform design and verification brief. Returns: mission, skill triggers, availability policy, Xcode preflight, design checks, build/test commands, and handoff requirements. Use before creating or changing SwiftUI, SwiftData, App Intents, Liquid Glass, or concurrency-sensitive UI. This tool does not run Xcode or mutate files.

• prepare_design_agent_brief

  Prepare a cost-aware design-agent brief before editing UI. Returns on success: JSON with mission, evidenceCommands, designRules, costControls, compatibility installs, MCP command, Agent Skills command, and handoffChecklist. Use this tool: as the first MCP call when a coding agent is asked to design, polish, audit, refactor, or generate interface code. It is local-first and does not call Figma, bro

• pull_design_system

  Pull the full design system from Figma (tokens, components, styles) into the local registry. Prereq: Figma bridge running + plugin connected \u2014 verify with check_bridge_health; start via `memi connect`. Returns: { tokens, components, styles, lastSync }. Errors: isError "Figma not connected" if no plugin. Run at session start or after designer changes; inspect results with get_tokens.

• pull_design_system_rest

  Pull the design system from Figma via REST API \u2014 no plugin or bridge required. Prereq: FIGMA_TOKEN and FIGMA_FILE_KEY env vars. Returns: { tokens, components, styles, lastSync }. Errors: missing env vars, or Figma API errors (403 = bad token, 404 = bad file key). Use in CI/headless; equivalent to `memi pull --rest`.

• research_design_package

  Preview a research-backed vibe design package from ResearchStore V2 plus an optional simulation run. Returns on success: { package } with brief, Atomic Design specs, evidence ids, Mermaid Jam-ready source artifacts, and warnings. This tool is non-mutating; call research_generate_specs to write specs or mermaid_jam_export to write FigJam source files.

• research_generate_specswrite action

  Write research-backed Atomic Design specs generated from ResearchStore V2. Prerequisites: Call research_design_package first to preview. This tool requires approved=true to make the write explicit. Writes DesignSpec, IASpec, PageSpec, ComponentSpec, and DataVizSpec objects through the Memoire registry.

• run_auditwrite action

  Run a deterministic design-system audit (WCAG contrast, token completeness, spec accessibility) and return structured findings. Prereq: none \u2014 token/spec level, no Figma, no AI. Returns: { success, results: issues[], score, level, summary }. focus="contrast" narrows to token contrast pairs; focus="skill-compliance" checks real source files against ATOMIC_DESIGN.md/MOTION_VIDEO_DESIGN.md's che

• scaffold_agent_design_files

  Preview or write a spec-first Atomic Design scaffold for agent-created files. Default is non-mutating: approved=false returns a dry-run JSON plan with the exact spec path, guardrails, and next generation commands. To write the spec, pass approved=true. This writes only the registry spec; generated code still requires generate_code or memi generate, so quality gates stay intact.

• scaffold_swiftui_files

  Preview or write a deterministic SwiftUI feature scaffold. Default approved=false is non-mutating and returns every planned path and file body: Memi iOS spec, SwiftUI view, optional screen model, preview, and Swift Testing file. Set approved=true only after reviewing the plan. Writes never alter Xcode project files and refuse to overwrite existing files.

• simulation_compare

  Compare completed simulation runs by adoption, confidence, evidence coverage, risk, and cost.

• simulation_costs

  Summarize token and cost usage for a simulation run.

• simulation_export_spec

  Convert a simulation report into a product-spec impact artifact that agents can paste into specs or handoff docs.

• simulation_generate_agents

  Generate a 20-60 agent model-swarm cohort from Memoire research evidence without starting a run.

• simulation_interview

  Interview a simulated product stakeholder from a completed local or model-swarm run.

• simulation_list_runs

  List persisted simulation runs with lightweight summaries. Use this to discover runIds for simulation_status, simulation_stream, simulation_transcript, simulation_costs, simulation_report, and simulation_compare.

• simulation_models

  List Codex-first model profiles available to Memoire model-swarm simulations. Live model execution is opt-in; unavailable providers automatically fall back to deterministic clean-room simulation.

• simulation_planwrite action

  Create a clean-room product simulation scenario from Memoire research evidence. Prereq: research/store.v2.json or a ResearchStore JSON string. Local TypeScript simulation core only; adapter=model-swarm plans Codex-first profiles with deterministic fallback. Returns: { scenario (agents, variables, graph, evidenceFindingIds), warnings }.

• simulation_report

  Export a simulation report with recommendations, risks, assumptions, events, interviews, and evidenceFindingIds.

• simulation_runwrite action

  Run a prepared local or model-swarm product simulation scenario. Prerequisites: Call simulation_plan first and pass the returned scenario.id. Returns on success: SimulationRun with status, events, eventCount, and persisted run id.

• simulation_run_matrixwrite action

  Plan and run multiple model-swarm hypotheses, then compare outcomes for product-spec decision work.

• simulation_status

  Read a local simulation run status from .memoire/simulations/runs.

• simulation_stream

  Read persisted simulation events in stream order. Paginated \u2014 use offset/limit to page through long runs instead of materializing the full event log.

• simulation_transcript

  Read model-swarm transcript memory for a run.

• sync_design_tokens

  Map registry tokens to a Tailwind theme.extend object; optionally import a W3C DTCG token file first. Prereq: tokens in the registry (pull_design_system first) \u2014 or pass dtcgFile to import them here. Never throws \u2014 returns {} when empty. Returns: partial theme (colors, spacing, fontSize, borderRadius, boxShadow) using var(--token) references; keys from the last token-name segment; "other

• update_tokenwrite action

  Update a design token value in the local registry, optionally pushing to Figma. Prereq: token must exist (names via get_tokens); Figma connection only for pushToFigma. Returns: { updated: true, name, pushedToFigma, reason? } \u2014 a requested-but-skipped or failed push is reported in reason, never silently dropped. Errors: isError if the token name is not found. For bulk Tailwind mapping use sync

• Code scan14 source files scanned25/25
• –Live reliabilityno gateway calls yet and no remote to proben/a
• –Tool poisoningtools not inspected (local package is not executed); not countedn/a
• Auth qualitylocal package, no credentials required12/15
• Maintenancelast push 16 days ago15/15
• Maintainer identitynamespace and repository owner differ4/10

memi: common questions

Is memi MCP server safe?

Yes, by our scan: it is graded A (86/100). Read the memi safety report

How do I install memi?

It runs on your machine. Copy the Claude Code, Claude Desktop or Cursor config from the install section.

Does memi need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is memi maintained?

The last commit was 16 days ago (2026-09-08). The latest release is v2.7.4.

What can I use instead of memi?

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