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excalidraw-room-mcp

by bjcoombs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

poll_room

Check a live Excalidraw room for new mentions, scene changes, or peer updates without loading the full canvas, so you can detect activity mid-task and decide whether to keep working or hand control back.

Instructions

Cheap state probe: connection state, sceneVersion, the peers, the ids and text of the pending mentions addressed to this agent, and whether the scene moved since a version you pass. Use it while you are working in a turn to notice a change without a full show_room; use wait_for_mention when you are handing the turn back to a person.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoText a note must contain to count as a mention. Omit it and this server answers to its own handle - "@<handle>", the handle room_status reports - and to "@claude", the broadcast tag every agent in the room hears; matching is case-insensitive. Pass a tag to match that text alone, which is how you read notes addressed to someone else.
sinceVersionNoA sceneVersion from an earlier call. changedSince is false only if the scene version still equals it.
answerAgentMentionsNoAlso return notes written by another agent in the room. False by default: a note stamped with another agent's handle is dropped, while notes people wrote (nothing stamps them) and this server's own notes are always returned. True returns them all, each with the 'from: <handle>' line naming its author - up to the room's agentReplyDepth, which bounds how far a chain an agent started may run before this agent stops hearing it. A chain a person started is never bounded.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.8.0
    • changedInput schema / properties / answerAgentMentions / description
      Previous value: -"Also return notes written by another agent in the room. False by default: a note stamped with another agent's handle is dropped, while notes people wrote (nothing stamps them) and this server's own notes are always returned. True returns them all, each with the 'from: <handle>' line naming its author."New value: +"Also return notes written by another agent in the room. False by default: a note stamped with another agent's handle is dropped, while notes people wrote (nothing stamps them) and this server's own notes are always returned. True returns them all, each with the 'from: <handle>' line naming its author - up to the room's agentReplyDepth, which bounds how far a chain an agent started may run before this agent stops hearing it. A chain a person started is never bounded."
  2. Changed3 schema fields changedv0.7.1
    • addedInput schema / properties / answerAgentMentions
      Added value: +{
+  "default": false,
+  "description": "Also return notes written by another agent in the room. False by default: a note stamped with another agent's handle is dropped, while notes people wrote (nothing stamps them) and this server's own notes are always returned. True returns them all, each with the 'from: <handle>' line naming its author.",
+  "type": "boolean"
+}
    • removedInput schema / properties / tag / default
      Removed value: -"@claude"
    • addedInput schema / properties / tag / description
      Added value: +"Text a note must contain to count as a mention. Omit it and this server answers to its own handle - \"@<handle>\", the handle room_status reports - and to \"@claude\", the broadcast tag every agent in the room hears; matching is case-insensitive. Pass a tag to match that text alone, which is how you read notes addressed to someone else."
  3. Addedv0.5.1

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and meets it: it discloses cost ('cheap'), non-mutating nature ('state probe'), the exact data returned, and the change-detection semantics. It also signals the intended call context, so an agent knows what will and won't happen.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler: the first front-loads the tool's value and output contents, the second gives usage direction. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is sufficient for correct selection and invocation: it enumerates return contents, explains the cheap-state-probe use case, names the relevant alternative, and the schema covers all parameters. No output schema exists, but the listed outputs give the agent enough to interpret the response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each parameter is already fully documented; the description itself adds little beyond rephrasing sinceVersion as 'a version you pass.' This meets the baseline for schema-covered parameters but does not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific purpose with a verb and resource ('Cheap state probe') and enumerates exactly what it returns: connection state, sceneVersion, peers, pending mention ids/text, and change detection. It also distinguishes itself from show_room and wait_for_mention, making sibling differentiation clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use it ('while you are working in a turn to notice a change without a full show_room') and when to use an alternative ('use wait_for_mention when you are handing the turn back to a person'). This gives actionable selection criteria beyond the schema.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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