dropbox / dropbox/mcp-server-dash

Add reproducible MCP safety receipt and CI/SARIF gate?

Open
#13 0 comments 0 reactions 0 assignees View on GitHub
Dominant language
Python
Stars
10
Forks
10
PR merge metrics
No merged PRs in 30d

Description

Hi Dropbox Dash MCP maintainers. I maintain [MCP Observatory](https://github.com/KryptosAI/mcp-observatory), an OSS tool for producing reproducible MCP server receipts, safe attack-readiness evidence, risk graphs, and GitHub Code Scanning/SARIF gates.

This repo is a good candidate because it exposes an enterprise-search MCP boundary and uses OAuth/API credentials, which downstream agent users will naturally want to review before depending on it in production.

I did **not** run anything against Dropbox services or credentials. The useful next step would be a no-secret fixture mode that can safely exercise startup/list_tools in CI, then add a weekly SARIF gate. The generated command would look roughly like:

```bash
npx @kryptosai/mcp-observatory setup-ci --all --command "uv --directory . run src/mcp_server_dash.py" --sarif --schedule weekly
```

A good PR could add:

- a no-secret fixture/mock mode for CI
- an MCP Observatory target config for that mode
- generated Markdown/JSON receipt evidence
- optional SARIF upload to GitHub Code Scanning

If you have a preferred safe startup command or fixture approach, I’m happy to open a focused PR around that. No vulnerability claim here; this is about giving agent users a reproducible trust receipt before wiring enterprise search into automated workflows.

Contributor guide

No contributing guide indexed for this repository

Research direction

Start with src/mcp_server_dash.py and the proposed `uv --directory . run src/mcp_server_dash.py` startup command. Define a no-secret fixture or mock mode that can exercise startup and list_tools in CI, then review how the MCP Observatory target, Markdown/JSON receipts, and optional weekly SARIF upload would be configured. Done means the safe CI path is reproducible without Dropbox services or credentials.

Written by the indexing model from the issue text.

Assessment

Tech stack
github-actions, python
Domain
ci-cd, security
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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