PyProc MCP turns public SPSE/Inaproc procurement data into MCP tools that can be used by LLM clients (Claude Desktop,...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Fresh repo activity plus visible builder pull. This is the kind of tool people test before it turns obvious.
Copy the install, test the workflow, then decide if it earns a permanent slot.
Reasonable to try, but it will take more than a quick skim to get real signal.
GitHub health 42/100. no security policy. 1 open issues make this testable, but not something to trust blind.
AI Agent
Cursor AI
Model
Claude
Fastest way to find out if pyproc belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
git clone https://github.com/wakataw/pyproc ~/.claude/agents/pyprocRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/pyprocNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ agents/ │ └─ pyproc/ ← installs here └─ settings.json
PyProc MCP turns public SPSE/Inaproc procurement data into MCP tools that can be used by LLM clients (Claude Desktop, Continue, Cursor), AI agents, automation workflows, Python scripts, and command-line users.
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: June 25, 2026
Repository state: Not marked archived
Honeystax upvotes are community interest signals, not star ratings. GitHub stars and repository health are source measurements; editorial risk and trial-cost notes are Honeystax analysis.