Grandma2 Mcp
C+ 73 completed
Other
cli / python · small
332
Files
74,319
LOC
1
Frameworks
9
Languages
Pipeline State
completedRun ID
#1546153Phase
doneProgress
0%Started
2026-04-16 23:48:32Finished
2026-04-16 23:48:32LLM tokens
0Pipeline Metadata
Stage
CatalogedDecision
proceedNovelty
41.67Framework unique
—Isolation
—Last stage change
2026-05-10 03:35:34Deduplication group #47298
Member of a group with 2,078 similar repo(s) — canonical #187349 view group →
Repobility · MCP-ready · https://repobility.com
AI Prompt
Create a command-line AI agent for controlling grandMA2 lighting consoles. I need this agent to expose 200 Model Context Protocol (MCP) tools, allowing AI assistants to drive the console via Telnet. The core should include an orchestrator, a task decomposer, and both working and long-term memory. Please implement a layered safety gate with `SAFE_READ`, `SAFE_WRITE`, and `DESTRUCTIVE` risk tiers. Additionally, integrate RAG-powered knowledge using three indexed sources: this repository, about 1,043 grandMA2 help pages, and the MCP SDK. The project should be built using Python and include pytest for testing.
python cli ai-agent lighting-control telnet mcp pytest rag
Generated by gemma4:latest
Catalog Information
Create a command-line AI agent for controlling grandMA2 lighting consoles. I need this agent to expose 200 Model Context Protocol (MCP) tools, allowing AI assistants to drive the console via Telnet. The core should include an orchestrator, a task decomposer, and both working and long-term memory. Please implement a layered safety gate with SAFE_READ, SAFE_WRITE, and DESTRUCTIVE risk tiers. Additionally, integrate RAG-powered knowledge using three indexed sources: this repository, about 1,0
Tags
python cli ai-agent lighting-control telnet mcp pytest rag
Quality Score
C+
73.4/100
Structure
85
Code Quality
74
Documentation
95
Testing
85
Practices
42
Security
45
Dependencies
90
Strengths
- Well-documented README with substantial content
- CI/CD pipeline configured (github_actions)
- Good test coverage (61% test-to-source ratio)
- Code linting configured (ruff (possible))
- Consistent naming conventions (snake_case)
- Properly licensed project
Weaknesses
- Potential hardcoded secrets in 3 files
- 2920 duplicate lines detected — consider DRY refactoring
- 10 'god files' with >500 LOC need decomposition
Recommendations
- Move hardcoded secrets to environment variables or a secrets manager
- Address 105 TODO/FIXME items — consider tracking them as issues
Languages
Frameworks
pytest
Symbols
function761
variable507
constant378
method228
class91
property9
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Add to your README:
BinComp Dependency Hardening
All packages →5 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.