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  3. Snowflake Labs MCP
Snowflake Labs MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 7:16:49 PM

Snowflake Labs MCP

User RatingsBe the first to rate and review this MCP server!Ownership verifiedThe owner proved control of this listing via a GitHub README, site badge, or DNS TXT record.
View Repository297 GitHub StarsTotal stargazers on GitHub for the source repository (297 stars).Visit Website

Deprecated MCP server for Snowflake enabling AI agents to query and manage structured/unstructured data with RBAC and SQL execution.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "snowflake-labs-mcp": {
      "command": "uvx",
      "args": [
        "snowflake-labs-mcp"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Alternatives๐Ÿ—„๏ธ More in Databases

Overview

This deprecated MCP server provided integration for Snowflake Cortex AI, allowing AI agents to query structured and unstructured data, manage Snowflake objects, execute SQL with permission controls, and query semantic views. It supported role-based access control and all Snowflake authentication methods. It is no longer maintained; users should migrate to the official Snowflake MCP server for active support and new features.

Use cases

โ€ขQuery unstructured data for retrieval augmented generation
โ€ขQuery structured data via semantic models
โ€ขManage Snowflake database objects (create, update, drop)
โ€ขExecute LLM-generated SQL with fine-grained permissions
โ€ขDiscover and query Snowflake semantic views

Key features

โ€ขSupport for Cortex Agent, Search, and Analyst services
โ€ขRole-based access control with fine-grained CRUD permissions
โ€ขConfigurable SQL statement execution permissions
โ€ขIntegration with Snowflake Python Connector for authentication
โ€ขObject management tools for common Snowflake objects
โ€ขSemantic view querying capabilities

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Snowflake Labs MCP.

Extracted Tool Capabilities
Support for Cortex Agent, Search, and Analyst services
Role-based access control with fine-grained CRUD permissions
Configurable SQL statement execution permissions
Integration with Snowflake Python Connector for authentication
Object management tools for common Snowflake objects
Semantic view querying capabilities

Documentation Overview

[DEPRECATED] Snowflake Cortex AI Model Context Protocol (MCP) Server

[!CAUTION] This project is deprecated and no longer maintained. Please migrate to the official Snowflake MCP Server. The official server is actively developed, fully supported by Snowflake, and continues to add new features.

This community MCP server previously provided tooling for Snowflake Cortex AI, object management, and SQL orchestration. It is no longer supported. For all new and existing use cases, please use the official Snowflake MCP Server instead.


Legacy documentation (for reference only)

The MCP server supported the below capabilities:

  • Cortex Search: Query unstructured data in Snowflake as commonly used in Retrieval Augmented Generation (RAG) applications.
  • Cortex Analyst: Query structured data in Snowflake via rich semantic modeling.
  • Cortex Agent: Agentic orchestrator across structured and unstructured data retrieval
  • Object Management: Perform basic operations against Snowflake's most common objects such as creation, dropping, updating, and more.
  • SQL Execution: Run LLM-generated SQL managed by user-configured permissions.
  • Semantic View Querying: Discover and query Snowflake Semantic Views

Getting Started

Service Configuration

A simple configuration file is used to drive all tooling. An example can be seen at services/configuration.yaml and a template is below. The path to this configuration file will be passed to the server and the contents used to create MCP server tools at startup.

Cortex Services

Many Cortex Agent, Search, and Analyst services can be added. Ideal descriptions are both highly descriptive and mutually exclusive. Only the explicitly listed Cortex services will be available as tools in the MCP client.

Other Services

Other services include tooling for object management, query execution, and semantic view usage. These groups of tools can be enabled by setting them to True in the other_services section of the configuration file.

SQL Statement Permissions

The sql_statement_permissions section ensures that only approved statements are executed across any tools with access to change Snowflake objects. The list contains SQL expression types. Those marked with True are permitted while those marked with False are not permitted. Please see SQL Execution for examples of each expression type.

Code
agent_services: # List all Cortex Agent services
  - service_name: <service_name>
    description: > # Describe contents of the agent service
      <Agent service that ...>
    database_name: <database_name>
    schema_name: <schema_name>
  - service_name: <service_name>
    description: > # Describe contents of the agent service
      <Agent service that ...>
    database_name: <database_name>
    schema_name: <schema_name>
search_services: # List all Cortex Search services
  - service_name: <service_name>
    description: > # Describe contents of the search service
      <Search services that ...>
    database_name: <database_name>
    schema_name: <schema_name>
  - service_name: <service_name>
    description: > # Describe contents of the search service
      <Search services that ...>
    database_name: <database_name>
    schema_name: <schema_name>
analyst_services: # List all Cortex Analyst semantic models/views
  - service_name: <service_name> # Create descriptive name for the service
    semantic_model: <semantic_yaml_or_view> # Fully-qualify semantic YAML model or Semantic View
    description: > # Describe contents of the analyst service
      <Analyst service that ...>
  - service_name: <service_name> # Create descriptive name for the service
    semantic_model: <semantic_yaml_or_view> # Fully-qualify semantic YAML model or Semantic View
    description: > # Describe contents of the analyst service
      <Analyst service that ...>
other_services: # Set desired tool groups to True to enable tools for that group
  object_manager: True # Perform basic operations against Snowflake's most common objects such as creation, dropping, updating, and more.
  query_manager: True # Run LLM-generated SQL managed by user-configured permissions.
  semantic_manager: True # Discover and query Snowflake Semantic Views and their components.
sql_statement_permissions: # List SQL statements to explicitly allow (True) or disallow (False).
  # - All: True # To allow everything, uncomment and set All: True.
  - Alter: True
  - Command: True
  - Comment: True
  - Commit: True
  - Copy: True
  - Create: True
  - Delete: True
  - Describe: True
  - Drop: True
  - Insert: True
  - Merge: True
  - Rollback: True
  - Select: True
  - Transaction: True
  - TruncateTable: True
  - Unknown: False # To allow unknown or unmapped statement types, set Unknown: True.
  - Update: True
  - Use: True

[!NOTE] Previous versions of the configuration file supported specifying explicit values for columns and limit for each Cortex Search service. Instead, these are now exclusively dynamic based on user prompt. If not specified, a search service's default search_columns will be returned with a limit of 10.

Connecting to Snowflake

The MCP server uses the Snowflake Python Connector for all authentication and connection methods. Please refer to the official Snowflake documentation for comprehensive authentication options and best practices.

The MCP server honors the RBAC permissions assigned to the specified role (as passed in the connection parameters) or default role of the user (if no role is passed to connect).

Connection parameters can be passed as CLI arguments and/or environment variables. The server supports all authentication methods available in the Snowflake Python Connector, including:

  • Username/password authentication
  • Key pair authentication
  • OAuth authentication
  • Single Sign-On (SSO)
  • Multi-factor authentication (MFA)

Connection Parameters

Connection parameters can be passed as CLI arguments and/or environment variables:

ParameterCLI ArgumentsEnvironment VariableDescription
Account--accountSNOWFLAKE_ACCOUNTAccount identifier (e.g. xy12345.us-east-1)
Host--hostSNOWFLAKE_HOSTSnowflake host URL
User--user, --usernameSNOWFLAKE_USERUsername for authentication
Password--passwordSNOWFLAKE_PASSWORDPassword or programmatic access token
Role--roleSNOWFLAKE_ROLERole to use for connection
Warehouse--warehouseSNOWFLAKE_WAREHOUSEWarehouse to use for queries
Passcode in Password--passcode-in-password-Whether passcode is embedded in password
Passcode--passcodeSNOWFLAKE_PASSCODEMFA passcode for authentication
Private Key--private-keySNOWFLAKE_PRIVATE_KEYPrivate key for key pair authentication
Private Key File--private-key-fileSNOWFLAKE_PRIVATE_KEY_FILEPath to private key file
Private Key Password--private-key-file-pwdSNOWFLAKE_PRIVATE_KEY_FILE_PWDPassword for encrypted private key
Authenticator--authenticator-Authentication type (default: snowflake)
Connection Name--connection-name-Name of connection from connections.toml (or config.toml) file

[!WARNING] Deprecation Notice: The CLI arguments --account-identifier and --pat, as well as the environment variable SNOWFLAKE_PAT, are deprecated and will be removed in a future release. Please use --account and --password (or SNOWFLAKE_ACCOUNT and SNOWFLAKE_PASSWORD) instead.

Transport Configuration

The MCP server supports multiple transport mechanisms. For detailed information about MCP transports, see FastMCP Transport Protocols.

TransportDescriptionUse Case
stdioStandard input/output (default)Local development, MCP client integration
sse (legacy)Server-Sent EventsStreaming applications
streamable-httpStreamable HTTP transportContainer deployments, remote servers

Usage

bash
# Default stdio transport
uvx snowflake-labs-mcp --service-config-file config.yaml

# HTTP transport with custom endpoint
uvx snowflake-labs-mcp --service-config-file config.yaml --transport streamable-http --endpoint /my-endpoint

# For containers (uses streamable-http on port 9000)
uvx snowflake-labs-mcp --service-config-file config.yaml --transport streamable-http --endpoint /snowflake-mcp

Transport Customizations

Server customizations available for sse and streamable-http transports:

ParameterCLI ArgumentEnvironment VariableDefault
Host--server-hostSNOWFLAKE_MCP_HOST"0.0.0.0"
Port--portSNOWFLAKE_MCP_PORT9000
Endpoint--endpointSNOWFLAKE_MCP_ENDPOINT/mcp
Debug Logging--verboseSNOWFLAKE_MCP_VERBOSEfalse

Example:

server.ts
export SNOWFLAKE_MCP_ENDPOINT="/my-mcp"
uvx snowflake-labs-mcp --service-config-file config.yaml --transport streamable-http

Using with MCP Clients

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
297
Stargazers on the source repository.
Last commit
3mo ago
Most recent push to the default branch.

Reviews

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Frequently Asked Questions about Snowflake Labs MCP

No, this project is deprecated and no longer maintained. Users should migrate to the official Snowflake MCP server.

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Technical Specs & Signals

Category๐Ÿ—„๏ธDatabases
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
Last updatedAug 7, 2026
10/11 checks healthy over the last 32d
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars297
GitHub Star CountTotal stargazers on GitHub representing community popularity (297 stars).
Last commit3mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on May 15, 2026
74Quality signal: Great ยท 74/100How this signal is calculated โ–พ
Server availability25/25
Verified ownership20/20
Documentation & tools23/30
Adoption & activity6/15
Community engagement0/10

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