tenets and meta-prompt-mcp-server

These tools are ecosystem siblings: one appears to be a local-first server designed to provide intelligent context to prompts, while the other transforms any MCP client into a multi-agent system via prompting, suggesting the latter could potentially leverage or integrate with the former's contextual feed.

tenets
51
Established
Maintenance 10/25
Adoption 4/25
Maturity 24/25
Community 13/25
Maintenance 2/25
Adoption 7/25
Maturity 15/25
Community 17/25
Stars: 7
Forks: 2
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 35
Forks: 9
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
No risk flags
Stale 6m No Package No Dependents

About tenets

jddunn/tenets

Local-first MCP server for intelligent context that feeds your prompts

This project helps software developers improve how they use AI coding assistants. It automatically finds and prioritizes relevant code files and project guidelines, then injects them into your AI prompts. Developers get more accurate and consistent AI suggestions without manually searching for context.

software-development AI-coding-assistant developer-productivity code-context-management coding-standards

About meta-prompt-mcp-server

tisu19021997/meta-prompt-mcp-server

Turn any MCP Client into a "multi-agent" system (via prompting)

This helps developers who want to use a large language model (LLM) to tackle complex programming tasks. It takes a problem description and a standard LLM, and transforms it into an AI "team" that breaks down the problem, delegates subtasks to specialized "experts" (like a Python Programmer or Code Reviewer), and produces a more robust solution. The output is a refined, multi-step solution to your coding challenge, making your LLM act like an organized project manager.

AI-assisted coding software development prompt engineering code generation problem solving

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