Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add christianclaudio/mcp-server-snowflake --skill snowflake-mcpgit clone --depth 1 https://github.com/christianclaudio/mcp-server-snowflakeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/christianclaudio/mcp-server-snowflake/snowflake-mcp)<a href="https://agentmods.dev/skills/christianclaudio/mcp-server-snowflake/snowflake-mcp"><img src="https://agentmods.dev/badge/skills/christianclaudio/mcp-server-snowflake/snowflake-mcp/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/christianclaudio/mcp-server-snowflake/snowflake-mcp"><img src="https://agentmods.dev/badge/skills/christianclaudio/mcp-server-snowflake/snowflake-mcp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.01454 |
| Opus 5 | $0.00023 | $0.00727 |
| Sonnet 5 | $0.00009 | $0.00291 |
| Haiku 4.5 | $0.00005 | $0.00145 |
Grade A, and why
snowflake-mcp scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Snowflake Data Cloud MCP Server (mcp-server-snowflake) Agent Skill
This skill provides expert operating guidelines, architectural recipes, and safety gates for AI agents orchestrating data workloads, schema management, virtual warehouses, streaming pipelines, and Cortex AI via mcp-server-snowflake.
🎯 Core Agent Recipes & Playbooks
1. Zero-Downtime Table Migration & Clones
- Step 1: Inspect Current Structure — Call
snowflake_inspect_table_with_sample(table_name=..., sample_rows=5)to verify columns, types, and data distribution. - Step 2: Instant Zero-Copy Backup — Invoke
snowflake_clone_table_recipe(source_table=..., target_table="..._BACKUP_YYYYMMDD"). Zero-copy clones create metadata pointers instantly without storage overhead. - Step 3: Apply Schema / DML Changes — Use
snowflake_execute_dml(statement=...)to alter table structures or populate new columns. - Step 4: Verify Data Profile — Run
snowflake_profile_table(table_name=...)to validate row counts and column completeness.
2. High-Performance Query Scaling
- Cost-Optimized Heavy Queries — Invoke
snowflake_warehouse_scale_and_execute(warehouse_name="COMPUTE_WH", target_size="LARGE", query="...", restore_previous_size=True). This scales compute up for the heavy workload and restores the previous size afterwards. It does not suspend the warehouse. To stop credit consumption, callsnowflake_suspend_warehousewhen the work is complete. - Query Optimization — Before running unknown queries, call
snowflake_get_query_plan(query=...)to inspect scan predicates and join pruning. After execution, analyzesnowflake_get_query_operator_stats(query_id=...).
3. Continuous Data Pipelines (CDC & Tasks)
- Change Data Capture — Create a stream via
snowflake_create_stream(stream_name=..., on_table=...). Read incremental delta changes withsnowflake_read_stream_changes(stream_name=...). - Scheduled Transformations — Deploy serverless or warehouse-backed tasks with
snowflake_create_task(task_name=..., sql_statement=..., schedule="15 MINUTE"). Resume the task withsnowflake_resume_task(task_name=...).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · +6 lines 8627f5f16d75
- 10d ago First seen · 65 lines · 45 tokens per session scan A 379a16972725
snowflake-mcp is a skill published in the GitHub repository christianclaudio/mcp-server-snowflake (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 45 tokens to every session and 1,454 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
map
Build and commit a Cortex function knowledge graph — maps structural dependencies and domain intent relationships across all AI functions in the project. Supports --reduce (default on) for transitive reduction of the dependency graph.
context-add
Guided wizard to capture or update organizational Snowflake/Cortex standards into .cocoplus/context/ .md. Presents a menu of 6 standard types, collects answers via multi-turn dialogue, and commits the file.
cocolean
CocoLean — minimum viable Cortex surface discipline. Pre-build decision ladder and intensity mode management. Invoke with $lean, $lean lite, $lean full, or $lean ultra.
map-diff
Analyze the impact of staged git changes against the committed Cortex function knowledge graph — shows which downstream functions are affected before you commit.
map-explain
Produce a natural-language explanation of a specific Cortex function, business capability, or schema element from the committed knowledge graph.
test
Enter the Test phase of CocoBrew. Reads spec.md test requirements, generates test cases, executes SQL validation and quality checks, records results in test.md. Can be re-run without full rebuild. Requires Build phase completion.