A privacy-preserving local RAG system integrated with MCP, enabling natural language queries over ingested documents and a SQLite database through vector search and local database tools.
Enables MCP agents to maintain durable, evidence-aware project knowledge, retrieve precise excerpts on demand, and track decisions, conflicts, and revisions across sessions.
Enables AI agents to store and retrieve provenance-aware facts with source, age, and boundaries, supporting search, read, propose, and local telemetry via MCP tools.
MCP server that enables AI agents to search, fetch, and analyze a self-maintaining markdown knowledge base with provenance, drift detection, and canonical definitions.
A semantic-memory MCP server that stores text 'memories' with provenance and enables recall by meaning (vector search), keyword (FTS5), or structured filters.