tenets and prompt-engineer-mcp-server

These two tools are competitors, both aiming to provide a local-first MCP server for prompt engineering, with "jddunn/tenets" emphasizing intelligent context feeding and "hireshBrem/prompt-engineer-mcp-server" focusing on a general prompt improvement utility.

tenets
51
Established
prompt-engineer-mcp-server
37
Emerging
Maintenance 10/25
Adoption 4/25
Maturity 24/25
Community 13/25
Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 16/25
Stars: 7
Forks: 2
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 13
Forks: 6
Downloads: —
Commits (30d): 0
Language: JavaScript
License: MIT
No risk flags
Stale 6m No Package No Dependents

About tenets

jddunn/tenets

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

Implements intelligent code context aggregation using NLP-based ranking (BM25, TF-IDF, embeddings, git signals) and automatically injects coding standards ("tenets") into prompts to maintain consistency. Exposes tools via Model Context Protocol to integrate natively with Cursor, Claude Desktop, Windsurf, and VS Code—all processing runs locally without external APIs.

About prompt-engineer-mcp-server

hireshBrem/prompt-engineer-mcp-server

Write 10x better prompts using Prompt Engineer MCP server.

Related comparisons

tenets and mcp-server-langfuse tenets and systemprompt-mcp-server tenets and meta-prompt-mcp-server tenets and promptz-mcp tenets and mcp-prompt-optimizer tenets and prompt-mcp-app

Scores updated daily from GitHub, PyPI, and npm data. How scores work