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 agentmods add instructions/foggy-projects/foggy-data-mcp-bridge-python/claude-mdgit clone --depth 1 https://github.com/foggy-projects/foggy-data-mcp-bridge-pythonWrote 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/foggy-projects/foggy-data-mcp-bridge-python/claude-md)<a href="https://agentmods.dev/instructions/foggy-projects/foggy-data-mcp-bridge-python/claude-md"><img src="https://agentmods.dev/badge/instructions/foggy-projects/foggy-data-mcp-bridge-python/claude-md.svg" alt="Measured on agentmods" 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 | $0.01259 | $0.01259 |
| Opus 5 | $0.00629 | $0.00629 |
| Sonnet 5 | $0.00252 | $0.00252 |
| Haiku 4.5 | $0.00126 | $0.00126 |
Grade A, and why
foggy-data-mcp-bridge-python 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 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Foggy Data MCP Bridge — Python
开源项目，请勿上传私有 key、账号密码、token 等敏感信息。
从 foggy-data-mcp-bridge (Java) 迁移的 Python 版语义层查询服务。
快速启动
cd foggy-python
# 安装依赖
pip install -e ".[dev]"
pip install aiomysql # MySQL 支持
# 运行测试
python -m pytest --tb=short -q
# 启动 MCP 服务（连接 Docker MySQL）
python -m foggy.demo.run_demo --port 8066
# 或指定数据库
python -m foggy.mcp.launcher.app --db-host localhost --db-port 13306 --db-user foggy --db-password foggy_test_123 --db-name foggy_test
项目结构
foggy-python/
├── src/foggy/
│ ├── core/ # 核心工具（异常、过滤器、工具类）
│ ├── bean_copy/ # Bean/Map 转换
│ ├── mcp_spi/ # MCP 工具接口
│ ├── dataset/ # 数据库层（方言、SQL 构建、ResultSet）
│ ├── dataset_model/ # 语义层引擎（定义、查询、元数据）
│ ├── fsscript/ # FSScript 脚本引擎
│ ├── mcp/ # MCP 服务器
│ │ ├── launcher/ # FastAPI 启动器
│ │ ├── routers/ # HTTP 路由（admin/analyst/mcp_rpc）
│ │ ├── schemas/ # 工具定义文件（从 Java 同步）
│ │ ├── spi/ # DatasetAccessor
│ │ ├── config/ # 配置（DataSource、Properties）
│ │ └── audit/ # 审计日志
│ └── demo/ # 演示模型和启动脚本
├── tests/ # pytest 测试（625+）
└── scripts/
└── sync_mcp_schemas.py # 同步 Java 工具定义
MCP 端点
| 路径 | 方法 | 说明 |
|---|---|---|
/mcp/analyst/rpc |
POST | MCP Streamable HTTP（JSON-RPC 2.0） |
/mcp/analyst/rpc |
GET | SSE 流 |
/api/v1/models |
GET | 列出所有模型 |
/api/v1/models/{name} |
GET | 模型元数据 |
/api/v1/query/{name} |
POST | 执行查询 |
/api/v1/query/{name}/validate |
POST | 验证查询（不执行） |
/health |
GET | 健康检查 |
/docs |
GET | Swagger UI |
MCP 工具（对齐 Java）
| 工具名 | 说明 | 状态 |
|---|---|---|
dataset.get_metadata |
获取所有模型和字段的 V3 元数据包 | ✅ |
dataset.describe_model_internal |
获取指定模型的详细元数据定义 | ✅ |
dataset.query_model |
执行数据模型查询（V3：支持 payload 格式） | ✅ |
dataset_nl.query |
自然语言查询 | ⏳ 需要 AI 服务 |
dataset.compose_query |
FSScript 多模型编排查询 | ⏳ |
chart.generate |
图表生成 | ⏳ 需要 chart-render-service |
dataset.export_with_chart |
查询+图表导出 | ⏳ |
dataset.inspect_table |
数据库表结构检查 | ⏳ |
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 First seen · 114 lines · 1,259 tokens per session scan A f1366047b4f1
foggy-data-mcp-bridge-python CLAUDE.md is an instructions file published in the GitHub repository foggy-projects/foggy-data-mcp-bridge-python (2 stars, last pushed 9d ago), licensed Apache-2.0. It adds 1,259 tokens to every session, about $0.0063 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 instructions, from other repositories
claude-tap AGENTS.md
Instructions for liaohch3/claude-tap, covering maintainer automation notes, agents 索引, documentation boundary, review guidelines and pre-commit hook.
full-stack-ai-agent-template CLAUDE.md
Instructions for vstorm-co/full-stack-ai-agent-template, covering claude.md, project overview, commands, install dependencies and run tests.
opencodex AGENTS.md
AGENTS.md instructions for lidge-jun/opencodex, covering agents.md, what this project is, repository layout, optional subsystems stay off the core path and the devlog directory.
goai AGENTS.md
AGENTS.md instructions for zendev-sh/goai, covering agents.md - goai, commands, architecture, key rules and adding providers.
Agent-Span AGENTS.md
AGENTS.md instructions for oxbshw/Agent-Span, covering agents.md, build & test, crate layout, adding a channel and adding an mcp tool.
gitlab-mcp-server mcp-best-practices.instructions.md
MCP protocol-level best practices for tool design, annotations, response formats, pagination, and security. Applies to all Go MCP server code.