memkin

Memkin is a local-first personal memory graph server providing AI agents with 36 MCP tools to read, write, and explore structured memories derived from chats, meetings, emails, and coding sessions.

🔍 Search & Retrieval

• query — Semantic/fuzzy search across all memory using natural language

• search — Exact keyword search for known identifiers or phrases

• get_page_context — Read a specific memory page with tags, links, backlinks, and timeline

• timeline_feed — Browse the global timeline with date, source, and keyword filters

• explore_graph — Traverse the knowledge graph to discover dependencies, collaborators, and related entities

🧠 Synthesis & Insights

• recall / synthesize — Generate cited, gap-aware summaries or composed answers from memory

• prep_for_person — Goal-conditioned communication strategy based on a person's passively inferred profile

• daily_report — Cross-channel daily report covering decisions, todos, completed work, pending replies, and reminders

• troubleshoot — Step-by-step playbook walkthrough for a given problem

• get_session_context — Load working memory summary at session start to quickly resume context

✍️ Writing & Memory Updates

• put_page — Create or idempotently update a durable memory page with markdown content

• add_timeline_entry — Append a dated event to an existing page

• manage_links — Add/remove directed graph relationships (e.g., mentions, depends_on) between pages

• manage_tags — Add/remove classification tags on memory pages

👤 Person & Entity Management

• get_entity_profile / list_signals_by_entity — Retrieve full profiles and all signals for people, projects, or tools

• link_person_alias / remove_person_alias / list_person_handles — Manage known aliases and handles

• merge_persons / recanonicalize_person — Merge duplicate person pages or rename canonical slugs

⚙️ System

• get_health — Check server status, page/chunk counts, MCP version, and capability flags

Allows bidirectional synchronization between Memkin's memory pages and an Obsidian vault, enabling editing of memory pages in Markdown and importing changes back.

Allows using a local Ollama instance for generating vector embeddings, keeping data fully private without external API calls.

Allows using OpenAI's API for LLM-based signal extraction and vector embeddings for the memory system.