# io.github.AvatarGaia/canvas-mcp (remote · agent.avatargaia.top)

TeamAgent Canvas MCP：13 个工具（岗位/商品/主题/活动等），支持远程 streamable-http 与 stdio 马甲。

- Trust score: 68/100 (medium)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-26

## Components

- remote · `agent.avatargaia.top`: 68/100 (this document), [markdown](https://verifymcp.io/servers/avatargaia-canvas-mcp/api-mcp-canvas.md), [page](https://verifymcp.io/servers/avatargaia-canvas-mcp/api-mcp-canvas)
- npm · `@avatargaia/canvas-mcp`: 49/100, [markdown](https://verifymcp.io/servers/avatargaia-canvas-mcp/avatargaia-canvas-mcp.md), [page](https://verifymcp.io/servers/avatargaia-canvas-mcp/avatargaia-canvas-mcp)

## Channel facts

- Endpoint: `https://agent.avatargaia.top/api/mcp/canvas`
- Transports: `streamable-http`
- Auth: `required`
- Version: `0.1.2`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-26.

- **Endpoint Security**: 57/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation not fully verified: no authorisation is required to call this server, and 13 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
  - HTTPS is enforced; there's no plaintext access path.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 71/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1972 tokens (~151/item across 13 items; 13 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 47/100
  - Stability observed for 14 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 77/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 32% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 13 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 13 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the io.github.AvatarGaia/canvas-mcp server?

io.github.AvatarGaia/canvas-mcp is a hosted endpoint at https://agent.avatargaia.top/api/mcp/canvas, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http avatargaia-canvas-mcp 'https://agent.avatargaia.top/api/mcp/canvas'
```

### Cursor

```json
{
  "mcpServers": {
    "avatargaia-canvas-mcp": {
      "url": "https://agent.avatargaia.top/api/mcp/canvas"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "avatargaia-canvas-mcp": {
      "type": "http",
      "url": "https://agent.avatargaia.top/api/mcp/canvas"
    }
  }
}
```

### Codex

```toml
[mcp_servers.avatargaia-canvas-mcp]
url = "https://agent.avatargaia.top/api/mcp/canvas"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "avatargaia-canvas-mcp": {
      "type": "remote",
      "url": "https://agent.avatargaia.top/api/mcp/canvas",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add avatargaia-canvas-mcp --url 'https://agent.avatargaia.top/api/mcp/canvas' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  avatargaia-canvas-mcp:
    url: "https://agent.avatargaia.top/api/mcp/canvas"
```

### Netclaw

```json
{
  "McpServers": {
    "avatargaia-canvas-mcp": {
      "Transport": "http",
      "Url": "https://agent.avatargaia.top/api/mcp/canvas"
    }
  }
}
```

### Vellum

```bash
assistant mcp add avatargaia-canvas-mcp -t streamable-http -u 'https://agent.avatargaia.top/api/mcp/canvas'
```

### Other

```json
{
  "mcpServers": {
    "avatargaia-canvas-mcp": {
      "type": "http",
      "url": "https://agent.avatargaia.top/api/mcp/canvas"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-25 (score 68, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-23 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-20 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-18 (score 65, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-16 (score 64, +1)

No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-14 (score 63, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-13 (score 62, +58)

- [security regression] HSTS header: unverified → fail
- [security improvement] Injection markers: unverified → pass
- [security improvement] TLS certificate: unverified → pass
- [security improvement] Transport: fail → pass
- [security] First check of Judged manipulation: pass
- [security] Authorization: Authorisation not fully verified: no authorisation is required to call this server, and 13 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
- [security] Tool “canvas_action” rewrote its description, which is the text the model reads
- [functional improvement] Tool coverage: unverified → 100
- [functional improvement] Stability: unverified → 0.03
- [functional improvement] MCP protocol: unverified → pass
- [functional] First check of Schema quality: fail
- [functional] First check of Tool coverage: 32
- [functional] First check of Schema quality: excellent
- [functional] First check of Destructive annotations: pass
- [functional] First check of Schema quality: fail

### 2026-09-12 (score 4)

First indexed and scored.

## MCP tools (13)

### `list_templates` (~103 tokens)

岗位模板清单

列出可开岗的数字员工模板。用于：想知道"系统能开哪些岗位"、或用户要开通新岗位时。返回每个模板的 templateId / 名称 / 说明 / canOpen / missingHandlers / 动作清单。别用它找"已开好的岗位"——那是 list_my_staff。canOpen=false 的模板不可开通（缺实现），别推荐用户选。参数：无。

### `list_my_staff` (~72 tokens)

我名下的岗位

列出我名下的数字员工岗位（slug / 名称 / 模板 / 画布链接）。用户问"我有哪些岗位"用它；后续所有按岗位操作的工具都要 slug，slug 一律从这里拿，不要凭记忆拼。参数：无。

### `open_canvas` (~258 tokens)

打开画布（拿链接和会话）

为岗位生成画布链接 + 会话 ID。用于用户需要"看得见的界面"（看报告/看商品/做检测）。参数：slug 必填；hostUserId 宿主用户标识（强烈建议带，会话归属和离线补推都靠它）；targetId 关爱/业务对象；app 指定画布页（如 aicare-kf）。返回 {url, session_id}——把 session_id 存下来，get_session_log / push_screen 都用它。会话在返回时已建立：现在就能 push_screen 给"还没来的人"备卡片，用户打开链接即补推；人打开后聊天/埋点都归到同一个 session_id。

Input parameters:

- `app` (string): 画布页面，默认岗位配置的；AICare 康护可传 aicare-kf
- `hostUserId` (string): 宿主系统的用户标识，如 AICare 的 userId
- `slug` (string, required): 岗位 slug（见 list_my_staff）
- `targetId` (string): 关爱对象/服务对象 ID（AICare 类岗位用）

### `get_staff_config` (~86 tokens)

读岗位配置

读岗位配置：personaPrompt / serviceFlow / promotionConfig / productSources / contextMode / layoutStyle / templateId / llmMode（只说是否 BYOK，不给密钥）/ tts。参数：slug 必填。改之前先读，否则会用"想当然的人设"覆盖客户调过的版本。

Input parameters:

- `slug` (string, required)

### `patch_staff_config` (~157 tokens)

改岗位配置

局部修改岗位配置，patch 只放要改的字段：personaPrompt(人设) / serviceFlow(服务流程，一行一步) / promotionConfig({categories:[{name,priority,url}]}) / productSources([{key,label,searchUrl,weAppId?,weAppUsername?}]) / layoutStyle(split|pip|classic) / contextMode(inline|webhook) / contextWebhookUrl / name。参数：slug、patch 都必填。这是写操作，改的是客户的岗位，改完立刻生效；不确定用户真要改时先复述一遍再调。

Input parameters:

- `patch` (object, required): 要改的字段
- `slug` (string, required)

### `list_actions` (~83 tokens)

岗位可用动作

列出这个岗位（按其模板）能做的动作：id / title / description / cost / credits / anonymous / job / params(JSON Schema)。参数：slug 必填。调 canvas_action 前先调它，不要猜 action 名——各岗位动作集不同，params 按它给的 schema 填。

Input parameters:

- `slug` (string, required)

### `canvas_action` (~387 tokens)

执行岗位动作

执行一个岗位动作（如 AICare 的 preflight / list_checks / gen_report / run_detection / resolve_user）。参数：slug、action 必填；params 按 list_actions 的 schema 填；session_id 想让结果落在某次会话里就带；hostUserId 宿主用户标识可选。返回 {ok, mode:"sync", data} 直接用；{ok, mode:"job", jobId, pollSec} 用 get_job 轮询。代价：list_actions 标 paid 的会从岗位出资人余额扣 credits（出报告 5 / 跑检测 2），失败不扣；同键（如同对象同一天）重复调用返回缓存结果（cached 标记）不重复扣，用户催第二次可放心重试。典型编排：list_actions → canvas_action(preflight) 拿背景 → canvas_action(gen_report) → get_job → 用自然语言讲给用户。公共岗位：gaia-academy（龙虾学院 · Agent 进修）的动作标 public:true——任何持有效 Key 的调用方都能跑，不需要拥有该岗位；学员身份取调用方 Key 的用户，非 public 动作对非归属方仍 403。典型用法：canvas_action(gaia-academy, search_courses → start_exam → submit_exam → get_principle)。

Input parameters:

- `action` (string, required): 动作 id，见 list_actions
- `hostUserId` (string): 宿主用户标识，可选
- `params` (object): 按 list_actions 给的 JSON Schema 填
- `session_id` (string): 可选，open_canvas 给的会话 ID，动作记录会挂到该会话
- `slug` (string, required)

### `get_job` (~88 tokens)

查长任务

按 job_id 查长任务：queued / running / done(带 result) / failed(带 error)。建议每 3 秒查一次。error 是人话（如"关爱对象不存在或已删除"），照原话转述给用户，不要改写成"系统繁忙"，也不要拿同参数重试。

Input parameters:

- `job_id` (string, required)

### `get_stats` (~113 tokens)

岗位统计

岗位一段时间的汇总：会话数、真人对话轮数、埋点数、动作调用数、tokens、按日曲线。参数：slug 必填；from/to ISO 时间，默认最近 30 天。用户问"这岗位最近怎么样/今天多少人来"就用它，不要靠聊天历史猜数字。需要有效 Key，匿名不开。

Input parameters:

- `from` (string)
- `slug` (string, required)
- `to` (string)

### `list_sessions` (~141 tokens)

会话列表

岗位的访客会话列表（最近优先）：session_id、宿主用户标识、轮数、时间。参数：slug 必填；q 按宿主用户标识模糊搜；from/to；limit；cursor 翻页传上一页返回的 nextCursor。想看"最近都服务了哪些人"用它，再拿 session_id 看明细。需要有效 Key，匿名不开。

Input parameters:

- `cursor` (string)
- `from` (string)
- `limit` (integer)
- `q` (string)
- `slug` (string, required)
- `to` (string)

### `get_session_log` (~112 tokens)

会话完整记录

单个会话按时间正序的完整流水：用户消息 / AI 回复(带 tokens) / 埋点 / 动作调用 / 推屏。参数：slug 和 session_id 两个都必填（slug 用于显式鉴权）。调用前先从 list_sessions 或 open_canvas 拿到合法 session_id。隐私边界：只能读自己岗位的记录。需要有效 Key，匿名不开。

Input parameters:

- `session_id` (string, required)
- `slug` (string, required)

### `query_events` (~148 tokens)

按类型查事件

跨会话按类型拉事件（倒序）：type = chat_user / chat_assistant / track / action_call / page_open / push。参数：slug 必填；type、from/to、limit(≤500)。每条带 source（mcp / page / server，看得出谁发起的）；action_call 的 payload 有 params/ok/ms/credits/cached/jobId——计费与排障的证据链；push 的 payload 有 preview。需要有效 Key，匿名不开。

Input parameters:

- `from` (string)
- `limit` (integer)
- `slug` (string, required)
- `to` (string)
- `type` (string)

### `push_screen` (~224 tokens)

推内容到画布

把内容推到某个画布会话的屏上。参数：session_id 必填（来自 open_canvas 或 list_sessions）；content 必填，写成一条"助手回复"文本，可含 ```canvas-md（Markdown 卡片）/ ```canvas-html（完整 HTML 文档）/ ```canvas（JSON 块）围栏，围栏外文字显示为字幕；speak=true 朗读字幕；title 可选。会话在线立即上屏；不在线（含还没人打开过的）存为待展示，该会话或同岗位同一 hostUserId 下次打开自动补推。屏属于会话不属于人：别复用别人的 session_id；要执行有副作用的动作（出报告/跑检测）用 canvas_action。需要有效 Key，匿名不开。

Input parameters:

- `content` (string, required): 含围栏的回复文本
- `session_id` (string, required)
- `speak` (boolean): 是否朗读围栏外文字
- `title` (string)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/avatargaia-canvas-mcp/api-mcp-canvas#diagnostics

## Score history

- 2026-09-26: 68
- 2026-09-25: 68
- 2026-09-24: 67
- 2026-09-23: 67
- 2026-09-22: 66
- 2026-09-21: 66
- 2026-09-20: 66
- 2026-09-19: 65
- 2026-09-18: 65
- 2026-09-17: 64
- 2026-09-16: 64
- 2026-09-15: 63
- 2026-09-14: 63
- 2026-09-13: 62
- 2026-09-12: 4

## Common questions

### What is the io.github.AvatarGaia/canvas-mcp server?

io.github.AvatarGaia/canvas-mcp is listed in the public MCP registry as io.github.AvatarGaia/canvas-mcp. TeamAgent Canvas MCP：13 个工具（岗位/商品/主题/活动等），支持远程 streamable-http 与 stdio 马甲。 This page covers its hosted endpoint (https://agent.avatargaia.top/api/mcp/canvas).

### Is the io.github.AvatarGaia/canvas-mcp server safe to use?

io.github.AvatarGaia/canvas-mcp scores 68 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the io.github.AvatarGaia/canvas-mcp server expose?

io.github.AvatarGaia/canvas-mcp exposes 13 tools: list_templates, list_my_staff, open_canvas, get_staff_config, patch_staff_config, and 8 more. Their descriptions and schemas cost roughly 1,972 tokens of context every time the server is loaded.

### Does the io.github.AvatarGaia/canvas-mcp server require authentication?

No. We connected to io.github.AvatarGaia/canvas-mcp without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the io.github.AvatarGaia/canvas-mcp server still maintained?

io.github.AvatarGaia/canvas-mcp is still listed as active in the MCP registry. We last reached this channel on 26 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://agent.avatargaia.top/api/mcp/canvas
- Authorisation metadata: https://agent.avatargaia.top/.well-known/oauth-protected-resource/api/mcp/canvas
- Repository: https://github.com/AvatarGaia/canvas-mcp
- Website: https://agent.avatargaia.top/
- Changelog RSS feed: https://verifymcp.io/servers/avatargaia-canvas-mcp/api-mcp-canvas.xml
- Changelog JSON feed: https://verifymcp.io/servers/avatargaia-canvas-mcp/api-mcp-canvas.json
- HTML version of this page: https://verifymcp.io/servers/avatargaia-canvas-mcp/api-mcp-canvas