MCP Tools Overview

BaseLayer exposes eleven tools via MCP. Any connected AI can call these to interact with your memory.

Querying

Tool	Purpose	When to use
ask_question	Synthesize answers with citations	Factual questions about you, your projects, preferences, and history

Searching & Exploring

Tool	Purpose	When to use
memory_search	Semantic search across entities and facts	Browsing, exploring, or discovering entities in your memory
get_entity	Fetch a full entity dossier	Deep dive into a specific person, project, plan, or concept
get_entity_relations	Browse graph edges and connections	Understanding how entities are linked, filtering connections
get_entity_provenance	Track fact origins	Verifying where knowledge came from, auditing sources
list_entities	Browse all entities of a type	Discovering what’s in your memory, finding plans
recent_conversations	Load recent dialogue context	Start of a conversation, catching up on recent activity
retrieve_evidence	Search raw conversation windows	Finding exact quotes, code snippets, or original wording

Writing

Tool	Purpose	When to use
record_memory	Persist observations and context	Saving decisions, notes, corrections, preferences
vault_fact	Assert precise facts in the graph	Creating specific entity relationships and edges
update_plan	Persistent markdown scratchpads	Tracking multi-step efforts across sessions

Common patterns

Start of conversation: The AI calls recent_conversations to load recent context, then uses ask_question as needed throughout the conversation. Factual questions: ask_question first for a synthesized answer with citations, then get_entity if more detail is needed on a specific entity. Research mode: memory_search to discover entities, then get_entity for full dossiers, then get_entity_relations to explore connections. Storing knowledge: record_memory for general notes and decisions, vault_fact for precise facts linking two entities. Plans: update_plan to create or update a persistent scratchpad, get_entity(type="plan") to read it back in any future session.

Tool priority order

When an AI needs to find information, it should follow this priority chain:

ask_question — always try this first for any factual query
memory_search — browse, explore, or find entities by type
get_entity — read a full dossier before acting on partial search results
retrieve_evidence — only when exact quotes or raw context are needed

How AIs use these tools

You don’t need to explicitly ask your AI to call these tools. Connected AIs use them naturally based on context:

If you ask about past work, the AI calls ask_question
If you share a decision, the AI calls record_memory
If you ask “what do you know about X,” the AI calls get_entity
If you start a multi-session effort, the AI creates a plan with update_plan

You can also explicitly request tool calls:

“Search my memory for anything about the Stripe integration.”

“Remember that we decided to use Redis for caching.”

“Create a plan to track the auth refactor.”

​MCP Tools Overview

​Querying

​Searching & Exploring

​Writing

​Common patterns

​Tool priority order

​How AIs use these tools