Aiconnect Figma MCP Server

aiconnect-figma-mcp npm v1.3.0

Published by guptaprakhariitr — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.

MCP server + Figma plugin that let AI agents read and edit Figma over a local WebSocket. AIConnect adds image/font/effect/gradient/SVG commands and a batch_ops command that builds whole pages in one round-trip.

Trust grade
A
96/100
Last scanned get badge →
Trust
A · 96/100
Adoption risk for you: the threat score, then adjusted down for blast radius, publisher verification and how much the scan could see. Deterministic; every point is auditable.
Capability
Moderate
Blast radius if it went rogue — what the server’s tools could reach. Independent of trust.
Coverage
Source
How much the scan could actually inspect. Shallow coverage is stated, never hidden.
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A Why this grade threat 100 − adoption risk = 96/100

The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.

1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:

The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.

2. Client adoption risk — 100 − 4 = 96. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:

PointsAdoption-risk factor
−3 capability blast radius (moderate) — client exposure if the model is manipulated
−1 publisher verification (public source) — no provenance, but the source is public and inspectable

Capability observations and info notes are shown under Findings but never scored. Open any row's finding below for the file, line and evidence behind a deduction.

Findings 3

medium Untrusted input can drive an external actionMTC-FLOW-005

Untrusted-input tools ([get_page_snapshot]) co-exist with external-action tools ([export_tokens]). A prompt injection could cause unwanted external actions, though no direct sensitive-data leak path was found.

Evidence: untrusted [get_page_snapshot] → sinks [export_tokens]

Fix: Require confirmation for state-changing/egress actions triggered after processing untrusted content.

Location: flow get_page_snapshot → export_tokens

medium Hardcoded egress to an external endpoint (dist/server.cjs)MTC-SRC-003

In the server's implementation (`dist/server.cjs:313`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.

Evidence: re"); const r = await fetch(`https://api.openverse.org/v1/images/?${params}`, { headers: { "User-Agent": "AIConnect-Fi

Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.

Location: server dist/server.cjs

medium Hardcoded egress to an external endpoint (dist/server.js)MTC-SRC-003

In the server's implementation (`dist/server.js:291`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.

Evidence: re"); const r = await fetch(`https://api.openverse.org/v1/images/?${params}`, { headers: { "User-Agent": "AIConnect-Fi

Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.

Location: server dist/server.js

Tools 69

Each tool and what it can reach — statically extracted from the published source.

  • export_tokensnetwork egress
  • get_page_snapshotingests untrusted input
  • apply_brandno sensitive capability
  • batch_opsno sensitive capability
  • bind_variableno sensitive capability
  • check_contrastno sensitive capability
  • clone_nodeno sensitive capability
  • create_component_instanceno sensitive capability
  • create_connectionsno sensitive capability
  • create_ellipseno sensitive capability
Show 59 more tools ↓
  • create_frameno sensitive capability
  • create_rectangleno sensitive capability
  • create_svgno sensitive capability
  • create_textno sensitive capability
  • create_variableno sensitive capability
  • create_variable_collectionno sensitive capability
  • delete_multiple_nodesno sensitive capability
  • delete_nodeno sensitive capability
  • export_node_as_imageno sensitive capability
  • fill_realistic_contentno sensitive capability
  • generate_paletteno sensitive capability
  • generate_themeno sensitive capability
  • get_annotationsno sensitive capability
  • get_console_logsno sensitive capability
  • get_cssno sensitive capability
  • get_document_infono sensitive capability
  • get_instance_overridesno sensitive capability
  • get_local_componentsno sensitive capability
  • get_node_infono sensitive capability
  • get_nodes_infono sensitive capability
  • get_reactionsno sensitive capability
  • get_selectionno sensitive capability
  • get_statusno sensitive capability
  • get_stylesno sensitive capability
  • get_variablesno sensitive capability
  • import_tokensno sensitive capability
  • insert_childno sensitive capability
  • insert_iconno sensitive capability
  • join_channelno sensitive capability
  • list_brand_presetsno sensitive capability
  • move_nodeno sensitive capability
  • read_my_designno sensitive capability
  • resize_nodeno sensitive capability
  • scan_nodes_by_typesno sensitive capability
  • scan_text_nodesno sensitive capability
  • search_iconsno sensitive capability
  • search_imagesno sensitive capability
  • set_annotationno sensitive capability
  • set_axis_alignno sensitive capability
  • set_corner_radiusno sensitive capability
  • set_default_connectorno sensitive capability
  • set_effectno sensitive capability
  • set_fill_colorno sensitive capability
  • set_focusno sensitive capability
  • set_font_nameno sensitive capability
  • set_gradient_fillno sensitive capability
  • set_image_fillno sensitive capability
  • set_instance_overridesno sensitive capability
  • set_item_spacingno sensitive capability
  • set_layout_modeno sensitive capability
  • set_layout_sizingno sensitive capability
  • set_multiple_annotationsno sensitive capability
  • set_multiple_text_contentsno sensitive capability
  • set_paddingno sensitive capability
  • set_selectionsno sensitive capability
  • set_stroke_colorno sensitive capability
  • set_text_contentno sensitive capability
  • set_variable_valueno sensitive capability
  • suggest_fontsno sensitive capability

Toxic flows 1

Cross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).

What this scan could not see

Versions 1

Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.

VersionScoreFindingsEngineScanned
v1.3.0 latest A 96/100 3 1.13.0 2026-09-08

Embed this score

Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.

MCP Trust Score: A · 96/100
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Verify this score yourself

The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.

npx mcptrustchecker scan aiconnect-figma-mcp --online

Use the free API → How scoring works

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