Borrowing it
Nothing to install: this file belongs to warrenzhu25/dataproc-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/warrenzhu25/dataproc-mcp/main/CLAUDE.mdgit clone --depth 1 https://github.com/warrenzhu25/dataproc-mcpWrote 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/instructions/warrenzhu25/dataproc-mcp/claude-md)<a href="https://agentmods.dev/instructions/warrenzhu25/dataproc-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/warrenzhu25/dataproc-mcp/claude-md/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/instructions/warrenzhu25/dataproc-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/warrenzhu25/dataproc-mcp/claude-md.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 | $0.00595 | $0.00595 |
| Opus 5.5 | $0.00238 | $0.00238 |
| Sonnet 5.5 | $0.00119 | $0.00119 |
| Haiku 4.5 | $0.00060 | $0.00060 |
Grade A, and why
dataproc-mcp CLAUDE.md 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 2mo 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dataproc MCP Server Development Guide
Build & Test Commands
Using uv (recommended)
- Install dependencies:
uv pip install --system -e . - Install dev dependencies:
uv pip install --system -e ".[dev]" - Update lock file:
uv pip compile --system pyproject.toml -o uv.lock - Install from lock file:
uv pip sync --system uv.lock
Using pip (alternative)
- Install dependencies:
pip install -e . - Install dev dependencies:
pip install -e ".[dev]"
Running the server
- Run server (stdio):
python -m dataproc_mcp_server - Run server with HTTP transport:
DATAPROC_MCP_TRANSPORT=http python -m dataproc_mcp_server - Run server with SSE transport:
DATAPROC_MCP_TRANSPORT=sse python -m dataproc_mcp_server - Run with MCP CLI:
mcp run src/dataproc_mcp_server/server.py - Run with debug logging:
DATAPROC_MCP_DEBUG=true python -m dataproc_mcp_server
Transport Configuration
- STDIO (default): Standard input/output communication for command-line tools
- HTTP: REST API over HTTP using streamable-http transport
- SSE: Server-Sent Events for real-time communication
- Set host/port:
DATAPROC_MCP_HOST=0.0.0.0 DATAPROC_MCP_PORT=8080
Testing and linting
- Run tests:
pytest - Run single test:
pytest tests/path/to/test_file.py::test_function_name -v - Run tests with coverage:
python -m pytest --cov=src/dataproc_mcp_server tests/ - Run linter:
ruff check src/ tests/ - Format code:
ruff format src/ tests/
Technical Stack
- Python version: Python 3.13+
- Project config:
pyproject.tomlfor configuration and dependency management - Environment: Use virtual environment in
.venvfor dependency isolation - Package management: Use
uvfor faster, more reliable dependency management with lock file - Dependencies: Separate production and dev dependencies in
pyproject.toml - Version management: Use
setuptools_scmfor automatic versioning from Git tags - Linting:
rufffor style and error checking - Type checking: Use VS Code with Pylance for static type checking
- Project layout: Organize code with
src/layout
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.
- 2mo ago First seen · 50 lines · 595 tokens per session scan A 88b6da865d55
dataproc-mcp CLAUDE.md is an instructions file published in the GitHub repository warrenzhu25/dataproc-mcp (0 stars, last pushed 1y ago), licensed MIT. It adds 595 tokens to every session, about $0.0024 per session on Opus 5.5. 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.
dataproc-mcp CLAUDE.md compared with instructions from other repositories
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|---|---|---|---|---|---|---|---|
| dataproc-mcp CLAUDE.mdwarrenzhu25/dataproc-mcp | Instructions file | 0 | 1y ago | MIT | A | 595 | Claude Code |
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