Freemium
Leading digital analytics platform for product insights and customer journey analytics
analyticsproduct analyticscustomer insights
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Pricing
Freemium
Use cases
Developers building context for AI coding assistants using local NLP-powered code ranking and analysis (verified: 2026-01-30), Engineers requiring a Model Context Protocol server to feed high-signal project data into LLM prompts (verified: 2026-01-30), Teams needing to distill specific code tasks into optimized context formats like HTML for analysis (verified: 2026-01-30)
Strengths
The tool performs all processing locally on the user machine to ensure codebase privacy without cloud APIs (verified: 2026-01-30), It utilizes multiple NLP techniques including BM25, TF-IDF, keyword extraction, and import graphs to rank code (verified: 2026-01-30), Users can access the functionality through multiple interfaces including a CLI, a Python library, and an MCP server (verified: 2026-01-30)
Limitations
The software requires a Python environment for installation via pip and specific dependency management for MCP features (verified: 2026-01-30), Core functionality is limited to local execution which necessitates sufficient local hardware resources for NLP analysis (verified: 2026-01-30)
Last verified
Jan 30, 2026
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Strengths
- The tool performs all processing locally on the user machine to ensure codebase privacy without cloud APIs (verified: 2026-01-30)
- It utilizes multiple NLP techniques including BM25, TF-IDF, keyword extraction, and import graphs to rank code (verified: 2026-01-30)
- Users can access the functionality through multiple interfaces including a CLI, a Python library, and an MCP server (verified: 2026-01-30)
Limitations
- The software requires a Python environment for installation via pip and specific dependency management for MCP features (verified: 2026-01-30)
- Core functionality is limited to local execution which necessitates sufficient local hardware resources for NLP analysis (verified: 2026-01-30)
FAQ
How does Tenets ensure that my private source code remains secure while using AI coding assistants?
Tenets operates with 100% local processing, meaning all NLP analysis and code ranking occurs directly on your machine. There are no cloud APIs involved and no data leaves your computer during the context building process, which eliminates the need for external API keys for core features (verified: 2026-01-30).
What specific technical methods does the tool use to identify the most relevant code for a task?
The system employs a variety of NLP-powered analysis techniques to find and rank code. These include BM25 and TF-IDF algorithms, keyword extraction, and the mapping of import graphs to provide high-signal context for LLM prompts (verified: 2026-01-30).
In what formats can I access the tool to integrate it into my existing development workflow?
Tenets is available as a Model Context Protocol (MCP) server, a Python library, and a Command Line Interface (CLI). This allows developers to install it via pip and use commands like tenets distill to generate optimized context (verified: 2026-01-30).
