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figjam-context-mcp

figjam-context-mcp

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
FIGMA_ACCESS_TOKENNoFigma personal access token. Can also be provided per-call via 'figmaAccessToken' input on ingest_board.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
ingest_boardA

Read a FigJam/Figma URL with the configured Figma token and persist a local snapshot for get_board_context, answer_from_board and diff_board; the summary names the largest sections to read next and how many excerpts lie outside sections. Leaves the Figma file unchanged. Every call downloads the board from Figma (one Tier 1 request); get_board_context and answer_from_board read the saved snapshot without a new request. Balanced/quality modes may send board text and images to the configured LLM provider and incur charges; max_speed skips vision. Re-ingest to refresh stale content and continue pending image interpretation; focusNodeIds with section IDs from the summary or the first page of get_board_context interprets their images first. Local history is bounded. Supports framework phases or customPhases.

get_board_contextA

Read source-cited context from an ingested board snapshot. Start overviews, summaries and documentation with a call without topic, nodeIds, limit and maxChars: its first page names the largest sections and lists sections with IDs. Then pass section, page, frame or group IDs as nodeIds; several IDs share each page in request order. For a whole-board summary, pass all top-level section IDs (at most 50 per call) with maxChars 24000, follow nextCursor, then read outsideSections: true. Default detail: "auto" switches reads of multiple distinct IDs or one page, section, frame or group to a compact overview only when the first full page would leave unread excerpts. Overview lines contain node IDs and deterministically shortened text (50–120 characters); structuredContent puts the excerpts once in overview.text, with empty evidence and clusters. limit applies only to the full view and is ignored in an overview, even when explicit. Read the complete source and Figma link with the same boardId and snapshotId, nodeIds: [""] and detail: "full"; table IDs read every row. Without overview, excerpts are in evidence. Read outsideSections: true, search with topic, or continue with cursor. Cite the node ID or Figma link behind each statement. Synthesize the answer yourself. No network or LLM calls; use ingest_board to refresh Figma content.

answer_from_boardA

Answer one specific question, such as a number, a status or a decision, from the most relevant excerpts of an ingested board, with validated source citations or an insufficient-evidence result. It finds excerpts by the question's words (whole words, ignoring case and accents (words of five or more letters also match compounds that begin with them); no other word forms, synonyms or translations), so ask with the board's words and language. Keep its citations (node ID and Figma link) with the statements they support. It reads only a handful of excerpts: not for summaries, lists, risks or next steps across several sections; read those with get_board_context. Sends the question and the selected excerpts to the configured LLM provider; calls may incur charges.

diff_boardA

Compare retained local snapshots of the same board, reporting cluster, node and connector changes. Names each changed node with its section and its old and new text, and each changed table cell with its row and column. Needs two ingests; when the board did not change in between, it reports no changes since the first. compareTo=1 selects the previous snapshot, 2 selects two states back. No network or LLM calls; ingest_board must capture the current Figma state first.

diagnose_llm_configA

Test the configured text and vision models with three small synthetic JSON challenges. Sends synthetic text and an image to the configured provider, may incur charges, and reports semantic/schema failures. Does not read board contents. Use after changing model/provider settings.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.3/5.0

Scored across 5 tools

Disambiguation4/5

Each tool maps to a distinct role: ingest (fetch snapshot), read/summarize (get_board_context), specific Q&A (answer_from_board), compare snapshots (diff_board), and config self-test (diagnose_llm_config). The main risk area is get_board_context vs answer_from_board, which both read from the same snapshot; the descriptions spend a lot of text partitioning them (summaries vs single factual questions), which mostly resolves the overlap but shows the boundary is not self-evident.

Naming Consistency4/5

All names are snake_case and verb-first (ingest_board, get_board_context, answer_from_board, diff_board, diagnose_llm_config). The verbs vary in form (plain verb, verb_prepositional, verb_object_object), but the pattern remains readable and predictable.

Tool Count5/5

Five tools is well-scoped for a board-snapshot context server: one write path, two read paths, one comparison, one diagnostics. No tool appears redundant or bolted on.

Completeness4/5

The lifecycle is covered: ingest, summarized/structured reading with cursors and search, targeted Q&A, snapshot diffing, and model diagnostics. Minor gaps exist around snapshot management (no explicit list/delete/prune of the bounded local history or snapshot inventory), but compareTo and re-ingest let agents work around these.

Maintenance

ActivityMaintained
ResponsivenessNo recent community issues