據 AlphaMoat 統計,截至 2026-09,Snowflake MCP Connection 累計下載 3,774 次、獲 3 個星標,在全部 5,078 個 AI 技能中排名第 2,812 位,在「運維安全」分類(264 個)中排名第 174 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 121 | 3664 | 3 | - |
| SkillHub ↗ | 129 | 3774 | 3 | — |
各平台的計數口徑不同,統計時間不一致。
該指南覆蓋 MCP 端點建立、身份驗證和工具連通性驗證,可供 Clawdbot 等客戶端連線 Snowflake。配置示例可能涉及高許可權角色、PAT 和可執行 SQL 的工具;應改用專用最小許可權角色,將憑據存入秘密管理或受保護環境,並只開放任務所需操作。寫入、管理或外發操作應預設關閉,確有需要時再經人工確認啟用。
資料釋出於 2026-10-29
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3774 | — | 3 |
| 2026-08 | 3578 | +2.3% | 3 |
| 2026-07 | 3496 | +8.3% | 3 |
| 2026-06 | 3228 | +4.2% | 3 |
| 2026-05 | 3099 | — | 3 |
| 2026-03 | 2585 | — | 3 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: snowflake-mcp description: Connect to the Snowflake Managed MCP server with Clawdbot or other MCP clients. Use when wiring Snowflake MCP endpoints, validating connectivity, or configuring Cortex AI services. --- # Snowflake MCP Connection Use this skill to integrate the Snowflake Managed MCP server with Clawdbot. It covers endpoint creation, authentication, and tool validation so Snowflake data can be accessed through MCP. ## Quick Start
### Prerequisites
- Snowflake account with ACCOUNTADMIN role
- Programmatic Access Token (PAT) from Snowflake
- Clawdbot or any MCP-compatible client
### Step 1: Create Programmatic Access Token (PAT)
1. In Snowsight, go to your user menu → **My Profile**
2. Select **Programmatic Access Tokens**
3. Click **Create Token** for your role
4. Copy and save the token securely
### Step 2: Create MCP Server in Snowflake
Run this SQL in a Snowsight worksheet to create your MCP server:
```sql
CREATE OR REPLACE MCP SERVER my_mcp_server FROM SPECIFICATION
$$
tools:
- name: "SQL Execution Tool"
type: "SYSTEM_EXECUTE_SQL"
description: "Execute SQL queries against the Snowflake database."
title: "SQL Execution Tool"
$$;
```
### Step 3: Test the Connection
Verify with curl (replace placeholders):
```bash
curl -X POST "https://YOUR-ORG-YOUR-ACCOUNT.snowflakecomputing.com/api/v2/databases/YOUR_DB/schemas/YOUR_SCHEMA/mcp-servers/my_mcp_server" \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--header "Authorization: Bearer YOUR-PAT-TOKEN" \
--data '{
"jsonrpc": "2.0",
"id": 12345,
"method": "tools/list",
"params": {}
}'
```
### Step 4: Configure Clawdbot
Create `mcp.json` at your project root (this is the MCP configuration Clawdbot can load for a session):
```json
{
"mcpServers": {
"Snowflake MCP Server": {
"url": "https://YOUR-ORG-YOUR-ACCOUNT.snowflakecomputing.com/api/v2/databases/YOUR_DB/schemas/YOUR_SCHEMA/mcp-servers/my_mcp_server",
"headers": {
"Authorization": "Bearer YOUR-PAT-TOKEN"
}
}
}
}
```
Start a new Clawdbot session and load `mcp.json` so the MCP connection is active. The Snowflake tools should appear in your session.
### Step 5: Verify in Clawdbot
1. Start a new Clawdbot session
2. Load `mcp.json` for the session
3. Ask a question that triggers Snowflake tools (for example, a SQL query)
## MCP Server Examples
### Basic SQL Execution Only
```sql
CREATE OR REPLACE MCP SERVER sql_mcp_server FROM SPECIFICATION
$$
tools:
- name: "SQL Execution Tool"
type: "SYSTEM_EXECUTE_SQL"
description: "Execute SQL queries against Snowflake."
title: "SQL Execution"
$$;
```
### With Cortex Search (RAG)
First create a Cortex Search service in Snowsight (AI & ML → Cortex Search), then:
```sql
CREATE OR REPLACE MCP SERVER search_mcp_server FROM SPECIFICATION
$$
tools:
- name: "Document Search"
identifier: "MY_DB.MY_SCHEMA.MY_SEARCH_SERVICE"
type: "CORTEX_SEARCH_SERVICE_QUERY"
description: "Search and retrieve information from documents using vector search."
title: "Document Search"
- name: "SQL Execution Tool"
type: "SYSTEM_EXECUTE_SQL"
description: "Execute SQL queries."
title: "SQL Execution"
$$;
```
### With Cortex Analyst (Semantic Views)
First upload a semantic YAML or create a Semantic View, then:
```sql
CREATE OR REPLACE MCP SERVER analyst_mcp_server FROM SPECIFICATION
$$
tools:
- name: "Sales Analytics"
identifier: "MY_DB.MY_SCHEMA.SALES_SEMANTIC_VIEW"
type: "CORTEX_ANALYST_MESSAGE"
description: "Query sales metrics and KPIs using natural language."
title: "Sales Analytics"
- name: "SQL Execution Tool"
type: "SYSTEM_EXECUTE_SQL"
description: "Execute SQL queries."
title: "SQL Execution"
$$;
```
### With Cortex Agent
```sql
CREATE OR REPLACE MCP SERVER agent_mcp_server FROM SPECIFICATION
$$
tools:
- name: "Documentation Agent"
identifier: "MY_DB.MY_SCHEMA.MY_AGENT"
type: "CORTEX_AGENT_RUN"
description: "An agent that answers questions using documentation."
title: "Documentation Agent"
$$;
```
### Full Featured Server
```sql
CREATE OR REPLACE MCP SERVER full_mcp_server FROM SPECIFICATION
$$
tools:
- name: "Analytics Semantic View"
identifier: "ANALYTICS_DB.DATA.FINANCIAL_ANALYTICS"
type: "CORTEX_ANALYST_MESSAGE"
description: "Query financial metrics, customer data, and business KPIs."
title: "Financial Analytics"
- name: "Support Tickets Search"
identifier: "SUPPORT_DB.DATA.TICKETS_SEARCH"
type: "CORTEX_SEARCH_SERVICE_QUERY"
description: "Search support tickets and customer interactions."
title: "Support Search"
- name: "SQL Execution Tool"
type: "SYSTEM_EXECUTE_SQL"
description: "Execute SQL queries against Snowflake."
title: "SQL Execution"
- name: "Send_Email"
identifier: "MY_DB.DATA.SEND_EMAIL"
type: "GENERIC"
description: "Send emails to verified addresses."
title: "Send Email"
config:
type: "procedure"
warehouse: "COMPUTE_WH"
input_schema:
type: "object"
properties:
body:
description: "Email body in HTML format."
type: "string"
recipient_email:
description: "Recipient email address."
type: "string"
subject:
description: "Email subject line."
type: "string"
$$;
```
## Tool Types Reference
| Type | Purpose |
|------|---------|
| `SYSTEM_EXECUTE_SQL` | Execute arbitrary SQL queries |
| `CORTEX_SEARCH_SERVICE_QUERY` | RAG over unstructured data |
| `CORTEX_ANALYST_MESSAGE` | Natural language queries on semantic models |
| `CORTEX_AGENT_RUN` | Invoke Cortex Agents |
| `GENERIC` | Custom tools (procedures/functions) |
## Benefits
- **Governed by Design**: Same RBAC policies apply as your data
- **No Infrastructure**: No local server deployment needed
- **Reduced Integration**: Connect any MCP-compatible client
- **Extensible**: Add custom tools via procedures/functions
## Troubleshooting
### Connection Issues
- **SSL Error**: Use hyphens instead of underscores in account name
- **401 Unauthorized**: Verify PAT token is valid and not expired
- **404 Not Found**: Check database, schema, and MCP server names
### Testing Tools
List available tools:
```bash
curl -X POST "https://YOUR-ACCOUNT.snowflakecomputing.com/api/v2/databases/DB/schemas/SCHEMA/mcp-servers/SERVER" \
-H "Authorization: Bearer PAT" \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}'
```
### PAT Token Notes
- PATs don't evaluate secondary roles
- Select a single role with all required permissions when creating
- Create new PAT to change role
## Alternative: Local MCP Server
For local deployment using the `snowflake-labs-mcp` package, see [mcp-client-setup.md](mcp-client-setup.md).
## Resources
- [Snowflake MCP Server Guide](https://www.snowflake.com/en/developers/guides/getting-started-with-snowflake-mcp-server/)
- [Snowflake MCP Documentation](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp)
- [GitHub: sfguide-getting-started-with-snowflake-mcp-server](https://github.com/Snowflake-Labs/sfguide-getting-started-with-snowflake-mcp-server)
- [MCP Protocol](https://modelcontextprotocol.io)
在使用技能包之前做安全掃描,並按結論決定放行或攔截的技能。
為 OpenClaw 配置 OpenRouter 免費模型與回退鏈的工具。
備份與恢復 OpenClaw 配置、憑據與工作區的技能。
設定並使用 1Password CLI 處理金鑰。
一款被描述為可偵測提示注入與危險命令的 OpenClaw 安全外掛。
遠端控制 tmux 會話,向互動式命令列傳送按鍵並抓取輸出。
以應用安全工程師視角做程式碼與架構的安全審計。
管理騰訊雲物件儲存與資料永珍的技能。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。