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by besslframework-stack • Uncategorized
An MCP server that captures, stores, and serves personal AI conversation knowledge locally across multiple AI tools.
Persistent memory across AI sessions to retain context and decisions.
Unify knowledge from multiple AI tools into a single local knowledge base.
Secure, encrypted local storage of AI conversation knowledge without relying on cloud services.
Tessera acts as a personal knowledge layer that automatically extracts and stores decisions, preferences, and facts from AI conversations, enabling cross-session memory and cross-AI portability. It supports integration with various AI tools like Claude, ChatGPT, Gemini, and Copilot, providing a unified knowledge base accessible via MCP or REST API. The system runs entirely locally with optional AES-256 encryption, ensuring privacy and no data leaves the user's machine.
Hybrid (semantic + keyword) search across indexed workspace documents (PRDs, decision logs, session logs, etc.). Call this tool first when the user asks about project-related content. Filter by project ID or doc_type (prd, session_log, decision_log, document).
Return full contents of a file as a structured view. CSV → markdown table, XLSX → tables per sheet, MD → raw text, DOCX → paragraphs. Use when the user wants to see the complete file, not just search results.
List all indexed source files.
Read file contents by absolute path.
Organize files in the workspace. action: 'move', 'archive', 'rename', 'list'. Always call suggest_cleanup first and get user confirmation before organizing.
Provide a browsable index of all indexed documents.
Provide current workspace status across all projects.
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